#  Executive summary

This document is the deliverable **“D1.4 – Data management plan v.2”** of the
European project “SIMPATICO - SIMplifying the interaction with Public
Administration Through Information technology for Citizens and cOmpanies”
(hereinafter also referred to as **“SIMPATICO”** , project reference: 692819).

The **Data Management Plan (DMP)** describes the types of data that has been
generated and/or gathered during the project, the standards used, the ways in
which data is exploited and shared (for verification or reuse), and in which
way data is preserved. This DMP has been prepared by taking into account the
template of the **“Guidelines on Data Management in Horizon 2020”** [Version
2.1. of 15 February 2016] and the EU General Data Protection Regulation
(GDPR).

The elaboration of the DMP allowed SIMPATICO partners to address all issues
related with data protection, including ethical concerns and security
protection strategy. SIMPATICO takes part in the **Open Research Data Pilot
(ORD pilot)** ; this pilot aims to improve and maximise access to and re-use
of research data generated by Horizon 2020 projects, such as the data
generated by the SIMPATICO platform during its deployment and validation.
Moreover, under Horizon 2020 each beneficiary must **ensure open access to all
peer-reviewed scientific publications** relating to its results: these
publications shall be made also available through the public section of the
SIMPATICO website. All these aspects have been taken into account in the
elaboration of the DMP.

A first version of the deliverable “D1.3 – Data management plan v.1” was
released at the beginning of the project (M6) and then updated at M16, after
the detailed definition of the project use-cases and the revision of the
ethics-related aspects of the project by the Ethics Advisory Board, and taking
into account the feedback collected during the 1  st  year project review.
This document represent the final version of the deliverable (M36) that takes
into account changes occurred in the last year of the project and reports the
final datasets produced.

Starting from a brief illustration of the SIMPATICO project, and of the
ethical concerns raised by the project activities, this report describes **the
procedures of data collection, storing and processing** , with a final
overview on **SIMPATICO security protection strategy** . The report also
reports on the datasets, language corpora and open publications produced by
the project during its lifetime.

This report does not cover the general concerns related to ethics and data
protection, as they are the focus of dedicated deliverables already submitted
– namely reports “D1.5 – Ethics compliance report” (including its final
version with the so-called GDPR Self-Assessment; see subsection 5.3 and

Annex 3 of the deliverable), “D8.1 – H – Requirement no. 1”, and “D8.2 – POPD
– Requirement no.

2”.

#  1\. Introduction

The research activities undertaken in the SIMPATICO project have important
data protection aspects, in particular due the foreseen involvement of
public/private stakeholders and citizens and due to the necessity to collect,
store and process personal data. This deliverable analyses the **data
management implications** of the activities undertaken in the project, and
describes the guidelines and procedures put in place in order to ensure
compliance with data management requirements.

The rest of this section provides **background information on the SIMPATICO
project** (Subsection 1.1) and identifies in brief the **ethical issues**
raised by the project activities (Subsection 1.2). The project aims **to
maximise access to and re-use of research data** , also ensuring **open access
to all peerreviewed scientific publications** relating to its results, in
order pave the path for its data management plan according to the signed Grant
Agreement - GA (Subsection 1.3.). Section 2 concerns the detailed
**description of SIMPATICO datasets** , according to the requirements set out
in Annex 1 - Data Management Plan template of the “Guidelines on Data
Management in Horizon 2020” [1]: (a) the handling of research data during and
after the project; (b) what data are collected, processed or generated; (c)
what methodology & standards have been applied; (d) whether data has been
shared/made open access and how; (e) how data has been curated and preserved.
Finally, Section 3 presents the **SIMPATICO security protection strategy** .

##  1.1. SIMPATICO in brief

SIMPATICO's goal is **to improve the experience of citizens and companies in
their daily interactions with the public administration** by providing a
**personalized delivery of** **e-services** based on advanced **cognitive
system technologies** and by promoting an **active engagement of people** for
the continuous improvement of the interaction with these services. The
SIMPATICO approach is realised through a platform that can be deployed on top
of an existing PA system and allows for **a personalized service delivery**
without having to change or replace its internal systems: a process often too
expensive for a public administration, especially considering the cuts in
resources imposed by the current economic situation.

The goal of SIMPATICO is accomplished through a solution based on the
**interplay of language processing, machine learning and the wisdom of the
crowd** (represented by citizens, business organizations and civil servants)
**to change for the better the way citizens interact with the PA. SIMPATICO**
**adapted** **the interaction process** to the characteristics of each user;
**simplify** text and documents to make them understandable; **enable feedback
for the users** on problems and difficulties in the interaction; **engage**
**civil servants, citizens and professionals** so as to make use of their
knowledge and integrate it in the system (Fig. 1).

Figure 1: SIMPATICO concept as a glance

The project aims can be broken down into the following **smaller research
objectives (ROs)** .

**RO1. Adapt the interaction process with respect to the profile of each
citizen and company** (PA service consumer), in order **to make it clear,
understandable and easy to follow** .

  * A **text adaptation** framework **,** based on a **rich** **text information layer** and on machine learning algorithms capable of **inducing general text adaptation operations** from **few examples, and of customizing these adaptations to the user profiles.**

  

  * **A workflow adaptation engine** that takes user characteristics and tailor the interaction according to the user’s profile and needs. 

  

  * A feedback and annotation mechanism that **gives users the possibility to visualize, rate, comment, annotate, document the interaction process** (e.g., underlying the most difficult steps), so as to provide valuable feedback to the PA, further refine the adaptation process and enrich the interaction. 

  

**RO2. Exploit the wisdom of the crowd to enhance the entire e-service
interaction process.**

  * An **advanced web-based social question answering engine (Citizenpedia)** where citizens, companies and civil servants **discuss and suggest potential solutions and interpretation for the most problematic procedures and concepts.**

  

  * A **collective knowledge** database on e-services that is used to simplify these services and improve their understanding. 

  

  * An **award mechanism** that **engages users and incentivize them to collaborate** by giving them **reputation** (a valuable asset for professionals and organizations) and **privileges** (for the government of Citizenpedia – a new public domain resource) according to their contributions. 

  

**RO3. Deliver the SIMPATICO Platform, an** **open software system that can
interoperate with PA legacy systems.**

  * A platform that **combines consolidated e-government methodologies with innovative cognitive technologies** (language processing, machine learning) at different level of maturity, enabling their experimentation in more or less controlled operational settings. 

  

  * An interoperability platform that enables an **agile integration of SIMPATICO’s solution with** PA legacy systems and that allows the exploitation of data and services from these systems with the SIMPATICO adaptation and personalization engines. **RO4. Evaluate and assess the impact of the SIMPATICO solution**

  

  * Customise, deploy, operate and evaluate the SIMPATICO solution on **three use-cases in two EU cities** – Trento (IT) and Sheffield (UK) – **and one EU region** – Galicia (ES). 

  

  * **Assess the impact** of the proposed solution in terms of **increase in competitiveness, efficiency of interaction and quality of experience.**

  

###  1.1.1. SIMPATICO technical framework and infrastructure

The SIMPATICO project intends to provide a **software platform** incorporating
technical innovations to enhance **the efficiency, effectiveness and
inclusiveness of public services** . To this aim, SIMPATICO collects,
generates and utilizes both personal and other data in a complex way. For what
concerns this deliverable (consumption, production and storage of data), the
key SIMPATICO components are the following:

  1. **Citizen Data Vault** : it represents the component that takes care of personal data exchange between a user and SIMPATICO components. It is a distributed repository of the citizen (or company) profile and related information. It is continuously updated through each interaction and is used to automatically pre-fill forms. In this way, the citizen gives to the PA the same information only once, as the information has been stored in the vault and used in all the following interactions; 

  

  2. **Human Computation (Citizenpedia):** SIMPATICO fosters citizens’ involvement, by providing Citizenpedia, a hybrid of Wikipedia and a collaborative question answering engine, and sharing improvements on public resources in a semi-automatic basis. Citizens, companies and civil servants discussed and suggest potential solutions and interpretation for the most problematic procedures and concepts. These interaction actions have been further refined the user profile and have been stored in the citizen data vault to serve as the basis for the adaptation of future interactions. Public servants are able to moderate comments and suggestions of citizenships to prevent crowd’s wisdom bias. The knowledge collected by a user on a specific e-service (e.g., a request of clarification or the explanation of a concept) can propagate and improve the understanding and interaction of potentially all users and eservices. An award mechanism that engages users and incentivize them to collaborate by giving them reputation (a valuable asset for professionals and organizations) and privileges is designed. 

  

  3. **SIMPATICO Adaptation Engine:** it is a cognitive system that makes use of innovative text processing and machine learning algorithms to adapt the text and the workflow of the interaction according to the user profile. The text adaptation engine adapts the text of the forms and of the other documents to make it more understandable and to clarify complex elements, while the workflow adaptation engine adapts the interaction process itself by presenting the citizen only the elements that are relevant for his/her profile (e.g., if the citizen is not a foreigner he/she has not been presented the section of a form reserved for foreigners). The adaptation engine exploits data collected on the interactions of the users, exploiting both implicit and explicit techniques; these data are stored in the “User Profile” and “Log” components of SIMPATICO. 

  

  

These components are highlighted in Figure 2, depicting SIMPATICO conceptual
architecture.

Figure 2: SIMPATICO Platform conceptual architecture and main components

###  1.1.2. SIMPATICO pilots

The piloting of the SIMPATICO platform is planned in two European cities (
**Trento and Sheffield** ) and one region ( **Galicia** ) in Italy, Spain and
the United Kingdom (UK), through a **two-phase use-case validation.** The
stakeholders engaged in the **three use-cases** were selected for their
experience and interest in e-services, as well as for the different socio-
cultural backgrounds of the three regions. In this way, the Consortium have
the opportunity to validate the effectiveness of the project results in
**contexts which differ on the number and heterogeneity of citizens and their
social and cultural background** . There are indeed important **differences in
the technological ecosystems** , with Trento and Sheffield having just started
the process of digitalization of their services to citizens and businesses
(this process happens in alignment and integration with the SIMPATICO
activities), and Galicia having a mature and consolidated e-service delivery
infrastructure (thus allowing to study the deployment of SIMPATICO on top of
an already operating system). The contexts also **differ for the point of view
of the number and heterogeneity of end-users and for the variety and maturity
of eservices** ( **see deliverable “D6.2 – Use-case planning & evaluation v2”
** ).

The tables below provide a short description of the SIMPATICO pilots
summarising the general background and purpose of the use cases, as well as
information on recruitment procedures, personal and sensitive data processing,
and vulnerable groups involved in the experimentations.  
  
<table>  
<tr>  
<th>

**TRENTO PILOT**

</th> </tr>  
<tr>  
<td>

**General background**

Trento is the capital of the Autonomous Province of Trento in Italy. It is a
cosmopolitan city of 117.317 inhabitants. The digitalization of all
interactions between the PA and its citizens is a priority for Trento, and the
city is currently working on a strategic project in this area. Trento has
already done much to improve interactions with its citizens. Trento has
already supported submitting applications through certified e-mail, by sending
the filled application documents and a scan of identity document and
signature. As part of its “smart city” strategy, Trento is working to realize
a new e-service portal: it serves as a “one-stop shop” or unique access point
that offers integrated and facilitated access to all the various services.
With this new portal, it is possible for citizens and businesses to
authenticate using smart service cards or one-time password devices, and to
complete the interaction online.

The Municipality of Trento has adopted “Sportello Telematico”, an end-to-end
solution provided by the GLOBO srl company, specifically targeting the
digitalization of modules for service provision by PA. Within this solution,
the digital module is a composition of sections of organic information (e.g.,
birth data section, residence data section, real estate registry data
section). The logic of the interaction with an information section is
explicitly mapped by the module designer. The integrations with legacy systems
are handle via a centralized REST web service, which routes the proper service
request to the right data source service. Finally the solution supports module
hierarchy, which guarantees the definition of a well organized digital module
library.

**Purpose of the use case**

The main specific purpose of the first SIMPATICO experiment phase in Trento is
to validate the integration between the Trento e-service portal and SIMPATICO
solution, with the final aim to evaluate the SIMPATICO solution usability. The
experiment has targeted the adoption of the SIMPATICO solution for all the new
e-services that has been published by the Public Administration during the
project lifetime.

**Recruitment procedures**

The experimentation is structured in two phases: (1) a pre-evaluation phase,
where the e-services and the SIMPATICO solution has been evaluated in a
controlled environment from a citizen panel representative of the e-service
user community; (2) an evaluation phase, where the e-services and the
SIMPATICO solution has been evaluated in a production environment and open to
everyone.

**Personal and sensitive data processing**

For both the above-mentioned e-services the project collected demographic
information from the participants (e.g., gender, age). More specifically, the
digital module of the childcare service requires to specify further personal
data (i.e., parent/custodial records, child records, family work conditions,
family economic conditions) and sensitive information (i.e., if the family is
in charge of the social care service; if the child has some form of
disability).

**Vulnerable groups**

Children, persons with disabilities, and immigrant or minority communities.

Please note that:

 the use case involved only participants capable to give consent (e.g., we
involved only the legal guardians and/or carers of children);

</td> </tr>  
<tr>  
<td>



</td>  
<td>

the Informed Consent Form has been translated in Italian;

</td> </tr>  
<tr>  
<td>



</td>  
<td>

appropriate efforts have been made to ensure fully informed understanding of
the implications of participation (i.e., participants shall understand all the
proceedings of the research, including risks and benefits).

</td> </tr> </table>  
<table>  
<tr>  
<th>

**GALICIA PILOT**

</th> </tr>  
<tr>  
<td>

**General background**

Galicia is an autonomous community of Spain and historic nationality under
Spanish law. It has a population of 2.717.749 inhabitants and has a total area
of 29.574,4 km. The Xunta de Galicia is the collective decision-making body of
the government of the autonomous community of Galicia. The Xunta has at its
disposal a vast bureaucratic organization based at Santiago de Compostela, the
galician government capital. According to data provided by IGE (Instituto
Galego de Estatistica), the number of Galician elderly inhabitants is
alarmingly increasing. Furthermore, the socioeconomic indicators for Galicia
show a number of particular needs that make it suited for eservices
improvement: a sparse distribution of the population, especially in the rural
parts of the region. In that regions people often migrate to the richer
coastal areas and other Spanish regions. This has resulted in large rural
areas with low population density, where the access to public services is
harder. Consequently, there is a big gap in the usage of e-services in Galicia
in the segment of population older than 55.

**Purpose of the use case**

The main specific purpose of the use case is to analyse and validate the
technological acceptance of elderly groups using the selected Xunta
("Government of Galicia") e-services and SIMPATICO solution. This analysis and
validation assessed both (1) discretionary usage and satisfaction to measure
the acceptance, and (2) the effectiveness and efficiency of the e-service
usage improved by SIMPATICO. The main target audience are the elderlies, and
three e-services have been selected:

  * Grants for the attendance to wellness and spas program; 

  

  * Individual grants for personal autonomy and complimentary personal assistance for disabled people. 

  

Assessment of degree of disability.

**Recruitment procedures**

This use case was a closed experimentation. The participants have been
recruited by three associations:

  * FEGAUS (Federation of Associations of alumni and ex alumni of the Senior University Programs) provides elder users. These users are between 55 and 75 years old. They have medium-high technological profile, i.e., they are able to autonomously access the internet and use modern devices such as smartphones and tablets. 

  

  * ATEGAL (Association for Lifelong Learning) provides elder users. These users are adults with age over 55 years, and with a medium cultural level. The technical level of the ATEGAL members is lower than that of the FEGAUS members. 

  

  * COGAMI is an association for people with disabilities of all ages. The technical level of the COGAMI members is heterogeneous, from entry-level users to experienced ones. 

  

</td> </tr>  
<tr>  
<td>

**Personal and sensitive data processing**

The project collected demographic information from the participants (e.g.,
gender, age) and whether they have physical disabilities (especially in the
case of COGAMI users).

**Vulnerable groups**

Elderly people and persons with disabilities. Please note that:

  * the use case involveed only participants capable to give consent (e.g., we involved only persons with physical disabilities); 

  

  * the Informed Consent Form has been translated in Spanish and Galician; 

  

  * appropriate efforts have been made to ensure fully informed understanding of the implications of participation (i.e., participants shall understand all the proceedings of the research, including risks and benefits). 

  

</td> </tr> </table>  
<table>  
<tr>  
<th>

**SHEFFIELD PILOT**

</th> </tr>  
<tr>  
<td>

**General background**

Sheffield is a city and metropolitan borough in South Yorkshire, England (UK).
It is England’s third largest metropolitan authority with 551.800 people.
Sheffield is an ethnically diverse city, with around 19% of its population
from minority ethnic groups. The largest of those groups is the Pakistani
community, but Sheffield also has large Caribbean, Indian, Bangladeshi,
Somali, Yemeni and Chinese communities. More recently, Sheffield has seen an
increase in the number of overseas students and in economic migrants from
within the European Union. It is estimated that migrants living in Sheffield
actively speak at least 40 languages. Although a significant volume of
information is openly available on the Sheffield City Council (SCC)'s website
(http://www.sheffield.gov.uk/), current interactions between migrants and
Sheffield City Council are mostly done in person or over the phone. An
intended outcome is that more users of council services will prefer to use
digital channels rather than traditional face to face, email and telephone
contact.

**Purpose of the use case**

The main specific purpose of the first SIMPATICO experiment phase in Sheffield
is to validate the implementation of the SIMPATICO technologies into the
Sheffield City Council website, with the final aim to evaluate the SIMPATICO
solution usability. The experiment has been based on three different
e-services:

  * School Attendance (i.e., it aims to inform parents, education workers and general citizens about the importance of school attendance by children. The following tasks presented in the page: information advising why school attendance is important; form to report suspected truancy; pay term time absence fine); 

  

  * Parenting Skills Course (i.e., it aims to inform parents about the support provided by the city council and external partners to equip them with better parenting skills); 

  

  * Young Carers (it aims to support and provide information for people under 21 who look after someone else. All young carers under 18 have the right to an assessment). 

  

**Recruitment procedures**

The Sheffield pilot has been delayed due to several organizational and
technical issues.

This caused the cancellation of the pre-evaluation phase for the phase two
evaluation and the

</td> </tr> </table>

delay of the evaluation until the last month of the project. At the time of
writing the Sheffield evaluation is being organized with the same structure of
the Xunta de Galicia Evaluation, that is a closed evaluation with no personal
data collected. For this reason Sheffield’s datasets are not release yet on
Zenodo like in the other two use-cases.

**Personal and sensitive data processing**

The project collects demographic information from the participants (e.g.,
gender, age) including sensitive information on ethnic or racial origin.

**Vulnerable groups**

Immigrants or minority communities, minors, possible persons with
disabilities.

Please note that:

  * the use case involve only participants capable to give consent (e.g., we involved only the legal guardians and/or carers of minors); 

  

  * the Informed Consent Form has been translated in English; 

  

  * translation services for immigrants or minority communities have been provided (when needed); 

  

  * appropriate efforts have been made to ensure fully informed understanding of the implications of participation (i.e., participants shall understand all the proceedings of the research, including risks and benefits). 

  

##  1.2. SIMPATICO ethical issues

The SIMPATICO consortium has been committed to **perform a professional
management of any ethical issue** that could emerge in the scope of the
activities of the project, also through the support of its **Ethics Advisory
Board** (see deliverable “D1.5 – Ethics compliance report”). For this reason,
the consortium has identified relevant ethical concerns already during the
preparation of the project proposal and, then, during the preparation of the
Grant Agreement. During this phase, the European Commission has also carried
out an ethics scrutiny of the proposal, with the objective of verifying the
respect of ethical principles and legislation. With regard to SIMPATICO, the
research entails specific ethical implications, involving human subjects and
risks for the protection of personal data [2] [3]. In particular, the
**SIMPATICO ethical issues (requirements)** , as reported in the European
Commission ethics scrutiny report and acknowledged by the SIMPATICO project,
are the following:

###  1.2.1. Protection of personal data – “D8.2 – POPD – Requirement no. 2”

  1. _Copies of ethical approvals for the collection of personal data by the competent University Data Protection Officer/National Data Protection authority must be submitted by the coordinator to REA before commencement of data gathering._

  

  2. _Clarification and if relevant justification must be given in case of collection and/or processing of personal sensitive data. Requirement needs to be met before commencement of relevant work._

  

  3. _The applicant must explicitly confirm that the existing data are publicly available._

  

  4. _In case of data not publicly available, relevant authorisations must be provided, requirements to be met before grant agreement signature._

  

  

SIMPATICO involves **collecting and processing personal data** (i.e., any
information which relates to an identified or identifiable natural person,
such as name, address, email) and **sensitive data** (e.g., health, sexual
life, ethnicity). The **Citizen Data Vault** represents the component that
takes care of personal and sensitive data exchange between a user and
SIMPATICO components. Personal and sensitive data has been and will be made
**publicly available** (e.g., for the data of **Citizenpedia** ) only after an
**informed consent** has been collected and suitable **aggregation and/or
pseudonymization techniques** have been applied. Mechanisms for encryption,
authentication, and authorization (e.g., TLS protocol, Single-Sign-On
implementations, Policy Enforcement Point for XACML) have been exploited in
the processes, so to ensure the satisfaction of core **security and data
protection requirements** , namely confidentiality, integrity, and
availability. For further details, please see sections below and deliverables
**“D1.5 – Ethics compliance report”** and **“D8.2 – POPD – Requirement no.
2”** .

The Consortium complies with the requirements of:a) the **Directive 95/46/EC**
of the European Parliament and of the Council of 24 October 1995 (and
subsequent modifications and supplements) on the protection of individuals
with regard to the processing of personal data and on the free movement of
such data; b) the **Regulation (EU) 2016/679** (General Data Protection
Regulation – GDPR) of the European Parliament and of the Council of 27 April
2016 on the protection of natural persons with regard to the processing of
personal data and on the free movement of such data, and repealing Directive
95/46/EC; ; c) the **national legislation** of SIMPATICO pilots (i.e., Italy,
Spain, and the United Kingdom) in the field  1  [4] (see also “D1.5 – Ethics
compliance report”).

In the context of the SIMPATICO project, Fondazione Bruno Kessler is the
**data controller** (i.e., the entity that is in control of the processing of
personal data and is empowered to take the essential decisions on the purposes
and mechanisms of such processing). **Data processors** (i.e., any partner
other than an employee of the data controller who processes the data on behalf
of the data controller) are all the other members of the SIMPATICO Consortium.

According to the new EU Regulation 2016/679, data subjects have a **right to
access and port data, to rectify, erase and restrict his or her personal data,
to object to processing** and, if processing is based on consent, **to
withdraw consent** . In particular, SIMPATICO complies with the GDPR as
follows:

  1. **Subject access, rectification and portability:**

     * FBK, as data controller, on request: confirms if they process an individual’s personal data; provides a copy of the data (in commonly used electronic form); and provides supporting explanatory materials; data subjects can also demand that their personal data be ported to them or a new provider in machine readable format; the request has been met within one month and any intention not to comply must be explained to the individual. Access rights are intended to allow individuals to check the lawfulness of processing and the right to a copy should not adversely affect the rights of others. 

  

     * For what concerns the personal data submitted by the user in the interaction with the eservices, the Citizen Data Vault provides users with explanations on how and which personal information has been collected during their interaction with e-services. At the first usage of CDV, users have been informed that at any moment, during their interaction with e-services, they can, by clicking appropriated buttons, withdraw the collection of data and export a copy of the collected data in an open format. Users have been asked to choose from two types of open format: CSV and JSON. 

  

  

  2. **Right to erasure (“right to be forgotten”) and right to restriction of processing:**

     * Individuals can require data to be "erased" when there is a problem with the underlying legality of the processing or where they withdraw consent; the individual can require the controller to "restrict" processing of the data whilst complaints (for example, about accuracy) are resolved, or if the processing is unlawful but the individual objects to erasure; FBK, as SIMPATICO data controller, who has made data available to other subjects, which is then subject to a right to erasure request, is required to notify others who are processing that data with details of the request. 

  

     * The Citizen Data Vault module has been designed to enable individuals to require data to be erased. Furthermore according to the "consent based" approach the user can at any moment withdraw the consent or to restrict the type of data stored by CDV during the interaction with e-services forms. 

  

  

  3. **Rights to object:**

     * There are rights for individuals to object to specific types of processing, such as processing for research or statistical purposes; 

  

     * SIMPATICO meets the obligations to notify individuals of these rights at an early stage through the informed consent form and its information sheet; 

  

     * Online services provided by the Pas involved in the project, and extended by the advanced techniques developed by SIMPATICO, offer their own methods of objecting. 

  

  

  

More information can be found in **D1.5 – Ethics compliance report.**

###  1.2.2. Humans - “D8.1 – H – Requirement no. 1”

  1. _Details on the procedures and criteria that will be used to identify/recruit research participants must be provided._

  

  2. _Detailed information must be provided on the informed consent procedures that will be implemented._

  

  

SIMPATICO involves **work with humans** (‘research or study participants’):
according to the EC, collection of personal data, interviews, observations,
tracking or the secondary use of information provided for other purposes. End-
users (i.e., citizens and businesses) are **engaged in the project usecases**
to test the functionalities provided by the SIMPATICO solution for the usage
of e-services. Specific **engagement campaigns** have been defined and
executed for each use-case. The use-cases involve **only voluntary
participants** **aged 18 or older and capable to give consent** , who have
been informed on the nature of their involvement and on the data
collection/retention procedures through an **informed consent form** before
the commencement of their participations. **Terms and conditions** have been
transparently communicated to the end-users by means of an **information
sheet** including descriptions of e.g., purpose of the research, adopted
procedures, data protection and privacy policies. SIMPATICO pilots involved
certain **vulnerable groups** , **e.g., elderly people, persons with physical
disabilities, and immigrants.** For further details, please see deliverables
**“D1.5 – Ethics compliance report”** and **“D8.1 – H – Requirement no. 1”** .

###  1.2.3. Vulnerable groups

In addition to the above-mentioned ethical requirements, in the context of
this deliverable it is also important to specify that SIMPATICO pilots
involved certain **vulnerable groups** : **e.g., elderly people, persons with
physical disabilities, and immigrants** . Please note that all the research
participants have the **capacity to provide informed consent** : individuals
who lack capacity to decide whether or not to participate in research have
been appropriately excluded from research. Anyway taking into account the
scope and objectives of the research, researchers should be **inclusive in
selecting participants** . Researchers did not exclude individuals from the
opportunity to participate in research on the basis of attributes such as
culture, language, religion, race, sexual orientation, ethnicity, linguistic
proficiency, gender or age, unless there is a valid reason for the exclusion.
Vulnerable groups could be misapplied for stigmatisation, discrimination,
harassment or intimidation. Concern for **the rights and wellbeing of research
participants** lies at the root of ethical review. The perception of subjects
as vulnerable is likely to be influenced by diverse cultural preconceptions
and so regulated differentially by localised legislation. It is likely to be
one of the areas where researchers **need extra vigilance to ensure compliance
with laws and customs** . Some vulnerabilities may not even be obvious until
research is actually being conducted.

To reduce the risk of enhancing the vulnerability/stigmatisation of the above-
mentioned individuals, the SIMPATICO **Ethics Advisory Board** (see below)
provided **specific assessment on vulnerable groups** that have been involved,
prior of the commencement of the pilots’ activities during its meetings in
2017/2018 and its final meeting. For further details, please see deliverables
**“D1.5 – Ethics compliance report”** and **“D8.1 – H – Requirement no. 1”** .

##  1.3. SIMPATICO Ethics Advisory Board

All the above-mentioned deliverables have been assessed and validated during
both the first meeting of the **SIMPATICO Ethics Advisory Board (EAB)** and
the subsequent meetings during the project lifespan (see “D1.5 – Ethics
compliance report”). The board is **competent to provide the necessary
authorizations** when the collection and processing of personal (or sensitive)
data is part of the planned research, with the validation of national and/or
local Data Protection Authorities if needed. This board is led by an **ethics
adviser** external to the project and to the host institution, totally
independent and free from any conflict of interest. In addition to the
external ethics adviser, the EAB was initially composed of **one expert
representative from all members of the SIMPATICO Consortium** [5]. After the
Review Meeting of May 18 2017, the Consortium was asked to change the
composition of the EAB adding **other two experts** to the board and ensuring
**gender balance** in decision-making. For these reasons, during the SIMPATICO
PMB meeting of June 22-23 2017, the PMB members identified possible experts
that were contacted during the month of July 2017\. The two new appointed
members participated firstly in the EAB meeting of November 30 2017.

Members of the Ethics Board are listed in “D1.5 – Ethics compliance report”
with the name and contact information for persons appointed, the terms of
reference for their involvement, and their declarations of no conflict of
interest. The **reference national and/or local Data Protection Authorities**
competent to provide the above-mentioned SIMPATICO EAB with the necessary
**instructions/authorizations/notifications** for each pilot are the following
[6] [7] [8]:

**Trento pilot (Italy): the Italian Data Protection Authority (DPA -
_http://www.garanteprivacy.it/_ )  . **

According to the “Italian Data Protection Code” (Legislative Decree no.
196/2003), an authorisation by the Italian DPA was required (before the entry
into force of the GDPR in May 2018) to enable private (and public) bodies to
process specific typologies of personal and sensitive data (see Section 26 of
the Italian Data Protection Code). More precisely, the DPA needs to be
notified (also thorough an electronic form) whenever a public or private body
undertakes a personal data collection, or personal data processing activity,
as data controller. A data controller was required under the law to only
notify the processing operations that concern e.g., data suitable for
disclosing health and sex life, data processed with the help of electronic
means aimed at profiling the data subject and/or his/her personality,
analysing consumption patterns and/or choices. SIMPATICO Data Controller sent
this notification on July 2016. In such context, the DPA is also responsible
for evaluating and expressing opinions on specific arguments concerning data
protection (see “Simplification of Notification Requirements and Forms.
Decision of the DPA dated 22 October 2008, as published in Italy's Official
Journal no. 287 of 9 December 2008”).

In the case of Trento pilot, we consider this public authority appropriate for
providing the SIMPATICO EAB with the necessary
instructions/authorizations/notifications.

###  Sheffield pilot (United Kingdom): the University Research Ethics
Committee (UREC) of the University of Sheffield

** ( _https://www.sheffield.ac.uk/ris/other/committees/ethicscommittee_ )  .
**

The University Research Ethics Committee (UREC) of the University of Sheffield
is an independent, unbiased and interdisciplinary university-wide body that
scrutinizes any potential issues related to research ethics for staff and
students of the University of Sheffield, including collaborative research
deriving from external funding. The key tasks this committee is in charge of
are:

  * Advise on any ethical matters in research that are referred to it from within the University; 

  

  * Keep abreast of the external research ethics environment and ensure that the University responds to all external requirements. 

  

In the case of the Sheffield pilot, we consider this committee appropriate for
providing the SIMPATICO EAB with the necessary guidance. We remark that all
entities involved in the Sheffield pilot – Sheffield Council, Sheffield
University and Sparta Technologies Ltd – comply with the UK data protection
regulations and GDPR, and eachs ensure that this act is enforced when it comes
to their participation in the pilot. Only if necessary, the EAB engages the UK
Information Commissioner's Office (ICO -  _https://ico.org.uk/_ )  .

**Galicia pilot (Spain): the Research Ethics Committee of the University of
Deusto (
_http://research.deusto.es/cs/Satellite/deustoresearch/en/home/research-
ethicscomittee_ )  . **

This committee is an independent, unbiased and interdisciplinary body that is
both consultative and advisory in nature, and reports to the Vice-Rector’s
Office for Research. This committee assessed SIMPATICO compliance with the
Spanish legal framework on privacy and data protection. This includes the
**Spanish Data Protection Act** 15/1999 ( **Law 15/1999 of 13 December 1999**
on Protection of Personal Data, last updated on 5 March 2011) and the **Royal
Decree 1720/2007** of 21 December 2007, approving the regulations implementing
Law 15/1999 (“Data Protection Regulations”; Last updated: 8 March 2012). Among
other responsibilities, this committee is in charge of:

  * Conducting the ethical assessment of research projects and drawing up the ethical suitability reports requested by institutions and researchers. 

  

  * Ensuring compliance with best research and experimentation practices with regard to individuals’ fundamental rights and the concerns related to environmental defense and protection. 

  

  * Supervising assessment processes or ethical requirements in research carried out by institutions and public bodies. 

  

  * Preparing reports for the University’s governing bodies on the ethical problems that may arise from R+D+I activities. 

  

  * Ensuring compliance with the Policy on Scientific Integrity and Best Research Practices of the University of Deusto. 

  

  * Providing guidance on laws, regulations and reports on research ethics. 

  

  * Reviewing procedures that have already been assessed, or proposing the suspension of any experimentation already started if there are objective reasons to do so. 

  

In the case of the Galicia pilot, we consider this committee appropriate for
providing the SIMPATICO EAB with the necessary
instructions/authorizations/notifications. Only if necessary, the EAB engages
the Spanish Data Protection Authority, i.e., Agencia Española de Protección de
Datos (AEPD -  _http://www.agpd.es/_ )  .

##  1.4. Open access and data management

The Consortium adheres to **the pilot for open access to research data (ORD
pilot)** adopting an open access policy of all projects results, guidelines
and reports, providing on-line access to scientific information that is free
of charge to the reader [9]. Open access typically refers to two main
categories: **scientific publication** (e.g., peer-reviewed scientific
research articles, primarily published in academic journals) (Subsection
1.3.1) and **research data** (Subsection  2  .3.2).

###  1.4.2. Open access to research data (Open Research Data Pilot)

According to the European Commission, “research data is information
(particularly facts or numbers) collected to be examined and considered, and
to serve as a basis for reasoning, discussion, or calculation”. Open access to
research data is **the right to access and reuse digital research data** under
the terms and conditions set out in the Grant Agreement.

Regarding the digital research data generated in the action, according to the
Article 29.3 of the GA, the SIMPATICO Consortium shall:

_**Deposit in a research data repository** and take measures to make it
possible for third parties to access, mine, exploit, reproduce and disseminate
— free of charge for any user — the following: _

  1. _the data, including associated metadata, needed to validate the results presented in scientific publications;_

  

  2. _other data, including associated metadata, as specified and within the deadlines laid down in this data management plan;_

  

  

_(i) provide information — via the repository — about tools and instruments at
the disposal of the beneficiaries and necessary for validating the results._

Please note that a portion of the relevant data for SIMPATICO comes from
**existing data sets of the PAs** (e.g., service usage data, citizens’ data),
while **new data sources** are defined by this deliverable and are identified
as a result of requirements analysis in SIMPATICO. **Whenever possible** ,
these additional data sources has also been made available **as open data or
through open services** . However, some of the collected data, in particular
that concerning **user profiles and personal data** , is highly sensitive and
has not been made available. More precisely, in order to discuss the **public
availability of data** , there are three different types of datasets within
the SIMPATICO project: 1. not publicly available personal and sensitive data;
2. data treated according to open access policy of all project results; 3.
data connected to Citizenpedia. These datasets are discussed in detail in
Section 2 below.

##  1.5. Data management policies

###  1.5.1. Data set reference and names

In order to be able to distinguish and easily identify data sets, each data
set is assigned with a unique name. This name can also be used as the
identifier of the data sets. In order to design the data set names, we use the
following practice. Each data set name consists of _four_ different parts
separated with a ”.” character:

_ProjectName.CountryCode.DatasetName.Version,_ where

  1. The _ProjectName_ is _SIMPATICO_ , in order to clearly identify for all datasets the origin. 

  

  2. The _CountryCode_ part represents the country associated with the dataset using ISO Alpha-2 country codes: 

    1. _IT_ for Italy ii. _ES_ for Spain iii. _UK_ for the United Kingdom 

  
  

  

  3. The _DatasetName_ represents the full name of the dataset. 

  

  4. The _Version_ of the dataset represents in which phase of the project the dataset was released: 

    1. _DB_ the live database during project lifetime 

  

    2. _InterimExport_ export of the database at M22 

  

    3. _FinalExport_ export of the database at the end of the project 

  
  

  

  

An example of a data set’s name is the following:
_SIMPATICO.IT.Citizenpedia.InterimExport._

###  1.5.2. Standards and metadata

This field describes suitable standards that are used to describe the data as
well as the metadata of the data sets. Metadata are “data that provides
information about other data”, describe the contents of data files and the
context in which they have been established. Several metadata standards exist
(see  _https://en.wikipedia.org/wiki/Metadata_standards_ )  . Proper metadata
facilitates use of the data by others, makes it easier to combine information
from different sources, and ensures transparency.

All SIMPATICO datasets use a standard format for metadata. Each dataset
description specifies the Data and metadata standards used.

###  1.5.3. Archiving and preservation

The SIMPATICO partners agreed on the procedures that have been and will used
in order to ensure long-term preservation of the data sets.

In particular, datasets have been stored on Zenodo (  _https://zenodo.org/_ )
a catch-all repository for EC funded research developed by CERN and launched
in May 2013\. To be an effective catch-all, that eliminates barriers to
adopting data sharing practices, Zenodo does not impose any requirements on
format, size (currently accepts up to 50GB per dataset), access restrictions
or license.

In addition, datasets stored on Zenodo are automatically part of OpenAIRE

( _https://www.openaire.eu/_ )  , the EC-funded initiative which aims to
support the Open Access policy of the European Commission via a technical
infrastructure, thus integrating them into existing reporting lines to funding
agencies like the European Commission. Archiving on Zenodo is free, thus
eliminating the costs.

###  1.5.4. Data quality assurance

SIMPATICO is committed to deliver quality data, and adopts **data quality
assurance** procedures to achieve this goal. Quality control of each dataset
is the responsibility of the relevant WP leader, supported by Project Manager
and Project Coordinator. Depending on the case, “quality” might have different
meanings, depending on the utility and on the re-usage scenarios of the
dataset: for instance, editing a question submitted by a citizen through the
SIMPATICO platform improves data quality if the goal is to provide an “FAQ” or
a knowledge base on public services; it is detrimental if the intended usage
is the analysis of interaction skills and languages of the platform users.
Data quality insurance might hence imply editing and moderation, cleaning,
pre-processing, adding metadata, transforming to a more convenient format or
providing easier access. Information about the consortium's efforts to address
data quality issues is hence provided for each type if dataset.

#  2\. SIMPATICO datasets

This **Data Management Plan (DMP)** has been prepared by taking into account
the current template of the “Guidelines on Data Management in Horizon 2020”
[1]. The elaboration of the DMP allows to SIMPATICO partners to address all
issues related with data. A first version of the DMP has been released at the
beginning of the project (M6). **This version is an update with the status of
the DMP at project month M16** , after the detailed definition of the project
use-cases and the revision of the ethics-related aspects of the project by the
Ethics Advisory Board, and taking into account the feedback collected during
the 1  st  year project review. A revised deliverable is expected at the end
of the project (“D1.4 – Data management plan v.2”, at M36). However, the DMP
will be a **living document** throughout the project, and this initial version
will evolve during the SIMPATICO lifespan according to the progress of project
activities.

In order to discuss the **public availability of data** , as outlined above,
it is convenient to distinguish three different types of datasets within the
SIMPATICO project:

  1. **Not publicly available personal and sensitive data** **will be collected and processed as part of the execution of the SIMPATICO use-cases** , more specifically for the execution of the eservices. Specifically, the use-cases will involve only voluntary participants aged 18 or older and capable to give consent, who will be informed on the nature of their involvement and on the data collection/retention procedures through an informed consent form before the commencement of their participations. Informed consent will follow procedures and mechanisms compliant with European and national regulations in the field on ethics, data protection and privacy (see also deliverables “D1.5 – Ethics compliance report”, “D8.1 – H – Requirement no. 1”, and “D8.2 – POPD – Requirement no. 2”). 

  

  2. **SIMPATICO adheres to the open access policy of all project results.** Specifically, we are committed to make available, whenever possible, the data collected during the execution of SIMPATICO, in particular data collected during the use-cases, also to researchers and other relevant stakeholders outside the project Consortium. Whenever possible, these additional data sources will also be made available as open data or through open services. In this context, any personal data will only be published after suitable aggregation and/or pseudonymization techniques have been applied, and after an informed consent that explicitly authorize this usage has been collected. 

  

  3. **SIMPATICO intends to build an open knowledge base on public services and processes** **through Citizenpedia** , released as a new public domain resource co-created and co-operated by the community (i.e., citizens, professionals and civil servants). The initial content of Citizenpedia will be based on datasets and other digital goods that are publicly available. In the case of datasets and other digital goods owned by the PAs and not already publicly available, the Consortium will pursue to obtain an authorization for public release, as open content, before inclusion in the Citizenpedia. For what concerns the data contributed to Citizenpedia by the community, SIMPATICO will require that they are made available as open content (e.g., with licenses such as Creative Commons). 

  

  

This Data Management Plan and its updated versions describe **datasets
characteristics** and **define principles and rules for the distribution of
data** within SIMPATICO. In particular, in this second version of the DMP we
present in details the procedures of creating **‘primary data’** (i.e., data
not available from any other sources) and of their management. As such, only
the datasets corresponding to “Citizenpedia” (Section 2.1), “Logging/Feedback”
(Section 2.2), and “Citizen Data Vault (CDV) Dataset” (Section  3  .3) are
described in detail in the following sections, as any other datasets already
exist and their creation is not foreseen in the GA.

##  2.1. Citizenpedia Datasets

###  2.1.1. Description

Citizenpedia is the **human computation framework** inside the SIMPATICO
platform. Its aim is to be a place where citizens can find useful information
regarding e-services and public administration. Thus, **most of the content is
created and consumed by humans** . It is mainly stored in JSON format.
Citizenpedia is composed of **two main interactive parts, which manage their
own data,** for the users, a Question Answering Engine and a Collaborative
Procedure Designer. Thus, the typology of data is twofold:

  1. **Question Answering Engine:** questions, answers, comments and terms/definitions, generated in the Question Answering Engine. All of them will be created, stored and retrieved in JSON format. 

  

  2. **Collaborative Procedure Designer:** diagrams representing procedures, and comments to these diagrams. The diagrams will be stored and encoded, in a computer processable manner, and not as a bitmap. Comments will be stored in JSON format. 

  

  

Both types of data is stored in the **same database** , within Citizenpedia;
for this reason, a unique datatset is generated for both data typologies.

Citizenpedia, along with the SIMPATICO platform, is deployed in **three
different cities/regions of different countries** (i.e., Italy, Spain, and the
United Kingdom). Each country speaks its own language (i.e., Italian,
Spanish,English and Galician), and the human-generated data in each
Citizenpedia is in **different languages** . For that reason, we are using a
different dataset in each pilot.

**Figure 3 Simplified Citizenpedia database model**

We consider **two types of additional metadata** to be generated in
Citizenpedia, apart from the core entities metadata mentioned above:

  1. **Usage statistics:** this information is created under demand. E.g. as an answer to the query “number of registered questions related to the Law XYZ/2015”. Currently, the Citizenpedia communicates with the LOG module to issue a new log every time a user performs a CRUD (Created, Read, Update, Delete) operation over any of the entities modeled by Citizenpedia. The LOG module offers an API from which usage statistics about Citizenpedia contents can be extracted. 

  

  2. **Indexing engine metadata:** an indexing engine included inside Citizenpedia, i.e. ElasticSearch or Apache SolR creates this data. This metadata is consumed by ElasticSearch to provide better searching capabilities over plain-text data. Search engine has been configured and parametrized in order to aim to optimize its searching capabilities. 

  

  

###  2.1.3. Data capture

As regards data capture methods, there are **two ways of creating content** in
Citizenpedia:

  1. **Using the web interface:** citizens/civil servants will use the platform and write the information using their browsers. Then, data will be stored in the Citizenpedia database. 

  

  2. **Programmatically, via a REST interface:** Citizenpedia exposes a REST API for other SIMPATICO components/third party applications to query/insert data in the system. 

  

  

###  2.1.4. Data storage

All the information related to Citizenpedia (i.e., both user-generated data
and metadata) is stored in the **Citizenpedia internal database** . DEUSTO, as
responsible of WP4 within the SIMPATICO Consortium, ensures to handle security
and privacy issues, enforcing access to the internal database only via
**secure connections** and using **access control systems** .

###  2.1.5. Data quality assurance

Data collection is undertaken mainly through forms filling through the QAE or
CPD. Both tools undertake validation against their type, semantics and
completeness. It is also possible to create data associated to the entities
managed by the Citizenpedia, namely User, Question, Answer, Comment,
Definition, Category, Tag, e-service, Procedure and Diagram Element, through
the provided RESTful API. Again, the same validation as when filling form
fields is carried out. For the last release of the Citizenpedia the following
two new features have been implemented to assure the quality of the data
managed. Firstly, a _spam analyser module_ have been included which assesses
whether the introduced contents can be regarded as spam, i.e. mainly for
questions and answers. Secondly, the _moderator role_ have been introduced to
ensure that some users can monitor, review and edit available updates,
correcting or even removing them in case that they are polluting rather than
enriching the Citizenpedia knowledgebase.

###  2.1.6. Utility and re-use

Data collected will be useful for Citizens and PA representatives. Citizens
can encounter answers regarding the contents and procedures associated to the
e-services that they interact with it. PA representatives can spot areas,
which are unclear for e-service consumers when gathering comments or new
questions associated to e-service concepts or procedure steps. Both QAE and
CPD can be used to ensure that a common understanding of e-service operation
is reached among PA representatives and with the e-service consuming citizens.

###  2.1.7. Data sharing

Method for data sharing is twofold:

  1. **Human generated data:** first, human generated data (such as questions/answers/comments) will be shared publicly. It could be checked using the web interface or programmatically through a REST API. Given that this data is created by users, they will be warned in their first time using Citizenpedia that any content they make will be publicly available. 

  

  2. **Metadata:** second, as regards the metadata generated from the usage of data (such as statistics), some of the statistics (aggregated data) will be publicly available through the REST API, e.g., the number of questions related to a certain topic. The entire metadata will only be used for research purposes: in the case of the releasing some scientific publication from the usage data of Citizenpedia, information will be completely aggregated and/or pseudonymized. 

  

  

###  2.1.8. Archiving and preservation

The SIMPATICO Consortium and, in particular, DEUSTO (as responsible of this
WP) consider **to** **retain generated data** during the length of the
project. Statistical data can be retained longer, after the end of the project
lifespan, for research purposes. If so, DEUSTO estimates no additional cost
for this. If collected metadata and statistical data will be retained after
the length of the project, DEUSTO has the infrastructure **to retain data
safely** .

###  2.1.9. Datasets  
  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_ES_Citizenpedia_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of Citizenpedia adopted by the Galician pilot

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

DEUSTO

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON database (MongoDB)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

500 Kb ~ 1 Mb

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Contents of this dataset can be accessed through Mongo binary API which can
only be used if proper credentials are supplied.

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Spanish deployment of SIMPATICO platform

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_ES_Citizenpedia_InterimExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Export of SIMPATICO_ES_CITIZENPEDIA_DB at the end of the first pilot phase
(M20).

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

DEUSTO

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

28.5 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years after project end

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2546817_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_ES_Citizenpedia_FinalExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Export of SIMPATICO_ES_CITIZENPEDIA_DB at the end of the project (M36).

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

DEUSTO

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

88.8 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years after project end

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2546438_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_UK_Citizenpedia_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of Citizenpedia adopted by the Sheffield pilot

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

SPARTA

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON database (MongoDB)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

500 Kb ~ 1 Mb (estimate)

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Contents of this dataset can be accessed through Mongo binary API which can
only be used if proper credentials are supplied.

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

UK deployment of SIMPATICO platform

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_UK_Citizenpedia_FinalExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Export of SIMPATICO_UK_CITIZENPEDIA_DB at the end of the project (M36).

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

SPARTA

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

500 Kb ~ 1 Mb (estimate)

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years after project end

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

This datasets has not yet been released, as the pilot evaluation in Sheffield
has been delayed to the last month of the project. Once released this dataset
will be stored on Zenodo.

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_IT_Citizenpedia_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of Citizenpedia adopted by the Trento pilot

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Fondazione Bruno Kessler

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON database (MongoDB)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

500 Kb ~ 1 Mb

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Contents of this dataset can be accessed through Mongo binary API which can
only be used if proper credentials are supplied.

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Trento deployment of SIMPATICO platform

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_IT_Citizenpedia_FinalExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Export of SIMPATICO_IT_CITIZENPEDIA_DB at the end of the project (M36).

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Fondazione Bruno Kessler

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

978.5Kb

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years after project end

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2554837_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>

##  2.2. Logging/Feedback Datasets

###  2.2.1. Description

The SIMPATICO project provides a series of interactive front-end components as
part of the user interaction and feedback analysis layer of the SIMPATICO
Platform. The components are as follows:

  * _Session Feedback (SF)_ : which presents users with a feedback gathering form after each session. 

  

  * _Data Analysis (DA)_ : which gets data from the LOG coming from a variety of sources connected to interaction and provides extra analysis layers on top. 

  

  * _Interaction Log (LOG)_ : which collects all the interaction information in the system. 

  

  * _Workflow Adaptation Engine (WAE)_ : which collects the interaction events derived from using the module to adapt the workflow in filling up long forms. 

  

These modules generate valuable information coming from the interaction of the
users. This happens by two different mechanisms:

  * **Explicit information gathering** , e.g., asking users directly to assess their interaction after it has happened. This is widely done in the industry and can be performed by a number of different mechanisms. 

  

  * **Implicit information collection** , e.g., analysing metrics of interest in the interaction without requiring the users to be providing any extra information. As an example, upon the execution of a e-service request information about the time spent for each step may be collected and then analysed to find insights such as bottlenecks. 

  

Both of these data generation sets were conceptualized in the platform’s
architecture in the cited modules. These includes **two data storage modules**
such as the LOG for explicit and implicit data plus a data analysis step in
the DA to generate new insights (e.g., statistics) from gathered data
elements.

###  2.2.2. Standards and Metadata

The SIMPATICO team has not found relevant dedicated standards about the
representation of these metadata. There is a model of the interaction (see
deliverable D3.2) which is the basis of the interaction in the project’s
results. Inspiration for this and other of the interaction elements such as
questionnaires, etc. is from common representation data models of usability
evaluation such as the System Usability Testing (SUS) [10], and standards such
as the ISO 9241  4  for desktop application ergonomics.

The metadata are generated from the data in the section above using the
following analysis steps:

**_Explicit information analysis:_ ** Statistics about general feelings or
ratings for particular areas or topics identified in the first stage of
analysis. This is chiefly generated by the Session Feedback component.

**_Implicit information analysis:_ ** Statistical analysis of the data
captured: average time spent by users, segmentation by age groups or target
groups, etc. This is captured in the front-end of the system and further
processed by the Data Analysis component.

###  2.2.3. Data capture

The data is collected in different ways according to the mechanism of
information gathering (i.e., implicit/explicit), as explained above:

**_Explicit information gathering (gathered in the Session Feedback
component)_ **

  * Questionnaires to the users with predefined (‘canned’) responses such as emoticons or “Likert scale” values. 

  

  * Open ended questions and free form responses. This can then be further analysed using NLP tools or human experts, to search for elements such as: 

  

o Sentiment analysis to capture the general sentiment generated by the system.
o Topic clustering to detect potential pain points or concerns of the users.

**_Implicit information gathering (gathered by the front-end and processed in
the Data Analysis_ _component)_ **

  * Capture metrics such as click areas, time spent in different steps of the process. For this matter a mixture of handcrafter trackers and the open web analytics tool Piwik are used. 

  

###  2.2.4. Data storage

The storage of these components (LOG/DA, SF, and WAE) is centralized at the
interaction LOG component which stores metadata of the interaction. This
component is constructed on top of an instance of the ElasticSearch.
Internally, ElasticSearch uses a document-oriented storage solution with an
associated Lucene indexing and search engine.

###  2.2.5. Data quality assurance

The results stored in the feedback analysis storage are stored as JSON
documents (Javascript objects in plain text). Internally, the data is
represented in manners which are specific to the application (e.g., feedback
logs from session feedback contain data that can be mapped to the specific
questions asked by the component).

The data stored can be related to individual users (linked to the ones in the
CDV by alphanumerical user IDs that mean the data is effectively anonymized if
the CDV profile is erased) or to aggregate results by a group of users (e.g.,
average times by all users to complete a step in the e-service).

The access to the LOG is securized by means of the use of the AAC component so
that arbitrary HTTP connections cannot be opened against the component.

###  2.2.6. Utility and re-use

By their nature, the feedback results compiled in this part of SIMPATICO, are
tightly connected to the particular usages and roles of the components. Thus,
their reuse can be difficult for other applications.

One result which can be of wider use is the global collection of
simplification requests. The simplification results and the feedback of the
users on the quality of the simplification as captured by the Session Feedback
component. This will be thus selected for further detailing and explanation in
the release of the data.

###  2.2.7. Data sharing

The data and metadata generated by the module expected to be useful beyond
SIMPATICO mainly to researchers due to the particularities of the application.
All of the generated data in the pilots is shared in the SIMPATICO Zenodo
Community as linked to in Section 2.2.9.

###  2.2.8. Archiving and preservation

**All storing and preservation procedures is carried out internally** to the
project (e.g., in servers physically located at the partners’ premises and
under their full control). The captured interaction data is shared as open
data.

Final data sets are shared using the Zenodo platform as referred to in the
next section. This will provide the means for long-term storage and sharing.
**2.2.9. Datasets**  
  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO First Evaluation Galicia Dataset v1.1

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Interaction LOG data captured in the Galicia evaluation of the results of
H2020 project SIMPATICO that were undertaken between October 23rd 2017 and
November 3rd 2017. This contains a total 374 user tests that were conducted,
divided into 228 citizens for e-service BS607A, 130 citizens for eservice
BS613B and 8 civil servants from Xunta de Galicia for each one of the
e-services.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

HIB

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation).

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

7.9 MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Full dump of the JSON log messages.

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

At least extended project duration (5 years after project execution ends).

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/1173125_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO Second Evaluation Galicia Dataset v1.0

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

SIMPATICO logs for the user evaluation of Galicia in project iteration 2 The
current package contains the Interaction LOG data captured in the Galicia
evaluation of the results of H2020 project SIMPATICO that were undertaken
between September 24th 2018 and October 15th 2018. This contains a total 290
user tests that were conducted in the period.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

HIB

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

9 MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Full dump of the JSON log messages.

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

At least extended project duration (5 years after project execution ends).

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2244751_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIPATICO_IT_LOGDataset_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of logs of the usage of SIMPATICO platform adopted by the Trento
pilot

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Fondazione Bruno Kessler

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation) and binary ElasticSearch dumps

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

10 KB /session /user (approximately). Totals: _Data size:_ 20 persons, 1
session 🡪 200 KB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Contents of this dataset can be accessed through swagger API

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Trento deployment of SIMPATICO platform

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIPATICO_IT_LOGDataset_FinalExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Released at the end of the final validation phase at Trento and project end
(M36) and including data from the interaction captured in the LOG.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Fondazione Bruno Kessler

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation) and binary ElasticSearch dumps

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

1.7Mb

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2554833_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIPATICO_UK_LOGDataset_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of logs of the usage of SIMPATICO platform adopted by the
Sheffield pilot

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

SPARTA

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation) and binary ElasticSearch dumps

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

10 KB /session /user (approximately). Totals: _Data size:_ 20 persons, 1
session 🡪 200 KB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

Contents of this dataset can be accessed through swagger API

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Sheffield deployment of SIMPATICO platform

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIPATICO_UK_LOGDataset_FinalExport

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Released at the end of the second validation phase at Sheffield (M36) and
including data from the interaction captured in the LOG.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

SPARTA

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific data

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

JSON (JavaScript Object Notation) and binary ElasticSearch dumps

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

(estimate) 10 KB /session /user

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

5 years

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

This datasets has not yet been released, as the pilot evaluation in Sheffield
has been delayed to the last month of the project. Once released this dataset
will be stored on Zenodo.

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>

##  2.3. Citizen Data Vault (CDV) Datasets

###  2.3.1. Description

The **Citizen Data Vault** **(CDV)** is a **repository of the citizen personal
data** . It is continuously updated through **each citizen interaction** and
is used mainly to automatically fill e-service forms. In this way, citizens
will give to the PA each information only once, as the information will be
stored in the vault and used in all the following interactions and among
different PA e-services. As regards the CDV, for personal data we will use the
**definition provided by the** **World Economic Forum (June 2010)** , namely
[11]:

**"Personal data is defined as data (and metadata) created by and about
people”** , encompassing:

  * **Volunteered data** – created and explicitly shared by individuals, e.g., social network profiles. 

  

  * **Observed data** – captured by recording the actions of individuals, e.g., location data when using cell phones. 

  

  * **Inferred data** – data about individuals based on analysis of volunteered or observed information, e.g., credit scores." 

  

Personal data is also very broadly defined in Article 2 of the European Data
Protection Directive as: "... any information relating to an identified or
identifiable natural person ("data subject")...". This definition is, for the
most part, unchanged under the new GDPR.

According to these definitions, through the CDV **citizens have a practical
mean to manage their personal data** with the ability to grant and withdraw
**consent** to third parties for access to data about themselves (see “D1.5 –
Ethics compliance report” – Annex I “Informed consent form”).

In summary, data collected by the means of CDV is referring on the context of
personal data. In a first stage, we have identified a **first categorization
of such personal data** , referring to:

  1. Government Records 

  

  2. Profile 

  

  3. Education 

  

  4. Relationship 

  

  5. Banking and Finance 

  

  6. Health 

  

  7. Communication & Media 

  

  8. Energy 

  

  9. Mobility 

  

  10. Activities 

  

  

For each category, **several data fields** have been defined. Starting from
these categories, we have grouped the actual personal data that each citizen
could manage by the means of CDV against the **three use cases** identified by
the three SIMPATICO pilots (i.e., Trento, Sheffield, and Galicia). The only
data that will be stored in CDV are those related to a subset of the fields of
PA e-service forms identified for the validation phases in the three pilots
use cases.

Below the list of services (e-service forms) selected by each pilot and the
type of data processed:

###  Trento Pilot Services  
  
<table>  
<tr>  
<th>

**Service**

</th>  
<th>

**Data Processed**

</th> </tr>  
<tr>  
<td>

DOMANDA ALLA

COMMISSIONE EDILIZIA COMUNALE CON FUNZIONE DI COMMISSIONE PER LA

PIANIFICAZIONE TERRITORIALE

E IL PAESAGGIO DELLA

COMUNITA (CPC)

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday, First Name,
Last Name, Street Address, Postal Code, City, Country, Province, Fax, Email,
Other Email, Phone Number, Work Industry,

Work Company, Work City, Work Province, Work Address, Work

Post Code, Work Post Code, Work VAT, Work PEC, Work Phone,

Work Fax, Work CCIAA, Work CCIAA Province, Work CCIAA Number

</td> </tr>  
<tr>  
<td>

ISCRIZIONE AL

INFANZIA

</td>  
<td>

NIDO DI

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

First Name, Last Name, Street Address, Postal Code, City, Country, Province,
Fax, Email, Other Email, Phone Number, Child Custodial Body, Child Custodial
Protocol, Child Custodial Date, Work Industry, Work Company, Work Province,
Work Address, Work Post Code,

Work Phone, Work Email, Work Revenue Agency, Work VAT

</td> </tr>  
<tr>  
<td>

DOMANDA

AUTORIZZAZIONE

PER ATTIVITA'

TEMPORANEA

</td>  
<td>

DI

ACUSTICA EDILIZIA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday, First Name,
Last Name, Street Address, Postal Code, City, Country, Province, Fax, Email,
Other Email, Phone Number, Work Industry, Work Company, Work City, Work
Province, Work Address, Work

Post Code, Work Post Code, Work VAT, Work PEC, Work Phone,

Work Fax, Work CCIAA, Work CCIAA Province, Work CCIAA Number

</td> </tr>  
<tr>  
<td>

DOMANDA DI

ACCESSO/CONSULTAZIONE

AGLI ATTI IN MATERIA EDILIZIA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

COMUNICAZIONE INIZIO

LAVORI

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday, Fax, Email,
Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

DEPOSITO DICHIARAZIONI DI

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

</td> </tr>  
<tr>  
<td>

CONFORMITA' DEGLI IMPIANTI

</td>  
<td>

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

COMUNICAZIONE OPERE

LIBERE

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

ISTANZA PER IL RILASCIO DI TITOLI EDILIZI PER ATTI DI

COMPRAVENDITA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country

</td> </tr>  
<tr>  
<td>

SEGNALAZIONE CERTIFICATA DI

INIZIO ATTIVITA'

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

RICHIESTA DI RIDUZIONE DELLA TARIFFA SUI RIFIUTI - I.S.E.E.

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

DICHIARAZIONE DI RESIDENZA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday, Fax, Email,
Other Email, Phone Number, Mobile Number, First

Name, Last Name

</td> </tr>  
<tr>  
<td>

TRASMISSIONE

DOCUMENTAZIONE

INTEGRATIVA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

Fax, Email, Other Email, Phone Number, First Name, Last Name,

Street Address, Postal Code, City, Country, Province

</td> </tr>  
<tr>  
<td>

ACCETTAZIONE POSTO AL NIDO

DI INFANZIA

</td>  
<td>

Citizenship, Sex, City of Birth, Social Security Number, Birthday,

First Name, Last Name, Street Address, Postal Code, City, Country,

Province

</td> </tr> </table>

**Galitia Pilot Services:**  
  
<table>  
<tr>  
<th>

**Service**

</th>  
<th>

**Data Processed**

</th> </tr>  
<tr>  
<td>

PROGRAMA BIENESTAR EN BALNEARIOS

</td>  
<td>

First Name, Last Name, Middle Name, Passport Number, Street Address,
Neighborhood, Place Name, Postal Code, City, Country,

</td> </tr>  
<tr>  
<td>

</td>  
<td>

Phone Number, Mobile Number, Email

</td> </tr>  
<tr>  
<td>

AYUDAS INDIVIDUALES PARA

PERSONAS CON

DISCAPACIDAD

</td>  
<td>

First Name, Last Name, Middle Name, Passport Number, Street Address,
Neighborhood, Place Name, Postal Code, City, Country,

Phone Number, Mobile Number, Email

</td> </tr>  
<tr>  
<td>

RECONOCIMIENTO DEL

GRADO DE DISCAPACIDAD

</td>  
<td>

First Name, Last Name, Middle Name, Passport Number, Street Address,
Neighborhood, Place Name, Postal Code, City, Phone

Number, Mobile Number, Email, Social Security Number

</td> </tr> </table>

**Sheffield Pilot Services:**  
  
<table>  
<tr>  
<th>

ADAPTING YOUR HOME

</th>  
<th>

Email, Phone Number, First Name, Last Name, Street Address, Postal Code,
Social Security Number, Birthday

</th> </tr>  
<tr>  
<td>

COST OF CARE

</td>  
<td>

Email, Phone Number, First Name, Last Name, Street Address, Postal

Code, Social Security Number, Birthday

</td> </tr>  
<tr>  
<td>

PARENTING SKILLS

WORKSHOP

</td>  
<td>

Email, Phone Number, First Name, Last Name, Street Address, Postal

Code, Social Security Number, Birthday

</td> </tr>  
<tr>  
<td>

FREE SCHOOL MEALS

</td>  
<td>

Email, Phone Number, First Name, Last Name, Street Address, Postal

Code, Social Security Number, Birthday

</td> </tr> </table>

We remark that the personal data collected or linked by the CDV will **never
be shared at any time** . **Each citizen** has the control and the ability to
have **a copy or** **removing all data from CDV** .

###  2.3.2. Standards and Metadata

CDV will collect personal data with a reference to a specific element of
**Personal Data Taxonomy** . In order to assure semantic interoperability
several options and tools are going to be considered, in particular **RDF and
Linked Data** [12], **XML and JSON** . In order to facilitate and promoting
interoperability among public services, in the context of CDV a working in
progress activity is standardize the Personal Data and Service Model taking
into account the e-Government Core Vocabularies created by ISA2 Programme.

###  2.3.3. Data capture

Personal data was collected in two ways:

  1. **Data is inserted by citizens by the means of the CDV dashboard.** The user is able to insert, collect and modify personal data fields by the means of interactive web forms provided by the CDV. 

  

  2. **Data is collected during the interactions of the user with the e-service forms provided by the PAs.** The e-services and the related types of data are the ones identified by the three pilots. During each interaction, users decide if the data inserted in the e-service forms can be stored in the CDV. 

  

  

At any time, users can **view (through the dashboard)** , and possibly
**remove the data collected** . No version of data collected is provided.
Thanks to the approach used to collect data, the stored information can be
**retrieved by using Personal Data Taxonomy** .

###  2.3.4. Data storage

The CDV provides an **ad-hoc repository to collect personal data** , adopting
a **multiple key based data encryption** . According to the specific
deployment strategy and the e-services adopted in each use case, the CDV
refers to **multiple data stores** (i.e., legacy systems just provided by the
PAs). Separated instances of CDV Data Store can be deployed for each use case
and hosted by each Pilot.

###  2.3.5. Data quality assurance

Data collection is based mainly on the e-services filling forms, provided by
PA and according its procedures and regulations. According to this, data
fields are validated against its type, semantics and completeness.

###  2.3.6. Utility and re-use

Data collected are useful for Citizen and PA. Citizen can collect personal
data during the interaction with e-services form, in order to reuse in all the
following interactions and among different PA eservices. PAs can facilitate
and enhance the interactions with citizen in their e-services.

**2.3.7. Data sharing**

The personal data collected or linked by the CDV will **never be shared at any
time** .

###  2.3.8. Archiving and preservation

SIMPATICO Project considers **to retain the collected personal data only for
the lifetime of the grant** .

In principle, the results are expected to be very use-case specific and **no
long-term storage is envisaged** beyond the needs for the SIMPATICO project
execution.

###  2.3.9. Datasets  
  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_IT_CDVTrento_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of CDV adopted by the Trento Municipality

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Trento Municipality

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific (JSON based)

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

RDF/JSON , ISA2 Core Vocabulary (WIP)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

4 Mb per User

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Private/Personal - no sharable

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

N/A

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Pilot hosting systems of SIMPATICO platform.

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_CDVSheffield_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of CDV adopted by the Sheffield Council

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

Sheffield Council

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific (JSON based)

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

RDF/JSON , ISA2 Core Vocabulary (WIP)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

4 Mb per User

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Private/Personal - no sharable

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

N/A

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Pilot hosting systems of SIMPATICO platform.

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_ES_CDVGalitia_DB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Live database of CDV adopted by the Galicia Region

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

HIB

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific (JSON based)

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

RDF/JSON , ISA2 Core Vocabulary (WIP)

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

4 Mb per User

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Private/Personal - no sharable

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

N/A

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Pilot hosting systems of SIMPATICO platform.

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>

##  2.4. Language Corpora

###  2.4.1. Description

During the project, several language corpora and data sets have been created
in order to _i)_ train or tune supervised systems for text adaptation and
simplification and _ii)_ evaluate them.

The data creation followed two main approaches: manual or (semi)-automatic.
Manual approaches are applied when high-quality data is needed and/or human
judgements are required, and have been used to create, for example, lexical
simplification benchmarks against which the different approaches have been
tested. In this case, annotators with linguistic background or a high language
proficiency have been involved to create a simplification of a complex
sentence, and mark the simplification type (e.g. insertion, deletion,
replacement, etc.).

(Semi)-automatic approaches, instead, have been used when it was necessary to
retrieve large amounts of monolingual data, or to align existing resources
automatically. For Italian, for example, starting from a large freely-
available corpus we automatically retrieved simple sentences to create a
monolingual collection of Italian sentences with high readability, which was
used to tune a system for neural simplification.

###  2.4.2. Standards and Metadata

The collected datasets and resources follow, when applicable, existing
standards for linguistic resources, which are generally XML-based. For large
training sets, also plain text corpora have been released.

###  2.4.3. Data capture

Data have been collected in different ways. The benchmarks have been manually
created, starting from existing complex sources (for example, text from
Sheffield City Council or Comune di Trento website), which have been
simplified and annotated.

The large training and tuning corpora have been automatically retrieved from
already available sources, see for example the monolingual simple sentences
for Italian extracted from the Paisà corpus (Lyding et al., 2014) or the
SubIMDB corpus for English (Paetzold and Specia, 2016).

###  2.4.4. Data storage

The different data sets are stored in publicly available repositories such as
Zenodo or github. Links to such resources are reported also in the
accompanying papers. The only exceptions are datasets for which no scientific
publications have been produced up to now. However, these datasets will be
publicly available after publication.

###  2.4.5. Data quality assurance

the benchmarks have been manually created or validated, ensuring high quality
of the annotation. As for the automatically retrieved or filtered data, small
inconsistencies are possible, which are described and explained in details in
the accompanying papers.

###  2.4.6. Utility and re-use

All language datasets are freely available for research purposes and can be
reused also beyond the project duration.

###  2.4.7. Data sharing

Data sharing is allowed. Benchmarks have been specifically created to ease
future research, so that novel systems for text simplification can be
evaluated using the SIMPATICO language data sets.

###  2.4.8. Archiving and preservation

As discussed at a project level, it is expected that data sets will be shared
using the Zenodo platform and/or github. This will provide the means for long-
term storage and sharing. **2.4.9. Datasets**  
  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_COMMON20LS

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Common20LS is a dataset for the task of Lexical Simplification that contains
demographic information about the annotators. It consists on 20 Lexical
Simplification problems annotated by 262 people. Each annotated instance is
composed of a sentence, a target complex word or phrase, and a set of
simplifications suggested by humans ranked by simplicity.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

12 MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

n/a

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2551474#.XFmQiVxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_BENCHPS

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

BenchPS is a dataset built for the training and evaluation of phrase
simplification systems. Each instance is composed of a sentence, target
complex phrase, and a set of candidate simplifications ranked by simplicity.
Each instance was annotated by humans through multiple annotations steps to
ensure the reliability of the data.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

147 KB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

n/a

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2551536#.XFmQtFxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_USERNN

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

We report three user studies in which the Lexical Simplification needs of non-
native English speakers are investigated. Our analyses feature valuable new
insight on the relationship between the non-natives’ notion of complexity and
various morphological, semantic and lexical word properties. Some of our
findings contradict long-standing misconceptions about word simplicity. The
data produced in our studies consists of 211,564 annotations made by 1,100
volunteers, which we hope will guide forthcoming research on Text
Simplification for non-native speakers of English.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

2.9MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_http://ghpaetzold.github.io/data/User_Studies_NNS.zip_

Zenodo -  _https://zenodo.org/record/2552816#.XFmRNFxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_SUBIMDB

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

SubIMDB is a corpus of everyday language spoken text we created which contains
over 225 million words. The corpus was extracted from 38,102 subtitles of
family, comedy and children movies and series, and is the first sizeable
structured corpus of subtitles made available.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

1GB and 972.2MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_http://ghpaetzold.github.io/subimdb/_

Zenodo -  _https://zenodo.org/record/2552407#.XFmRI1xKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_NNSEVAL

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Evaluating Lexical Simplification for Non-Native. 400 non-native speakers were
asked to judge whether or not they could understand the meaning of each
content word in a set of sentences, each of which was judged independently. A
total of 35,958 distinct words from 9,200 sentences were annotated (232,481
total), of which 3,854 distinct words (6,388 total) were deemed as complex by
at least one annotator.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

27.4 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_http://ghpaetzold.github.io/data/NNSeval.zip_

Zenodo -  _https://zenodo.org/record/2552381#.XFmRiVxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_BENCHLS

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

This is a dataset for Lexical Simplification which contains 929 instances,
with an average of 7.37 candidate substitutions per complex word. BenchLS is a
combination of two resources: the LexMTurk (Horn et al., 2014) and LSeval (De
Belder and Moens, 2012) datasets. The instances in both datasets contain a
sentence, a target complex word, and several candidate substitutions ranked
according to their simplicity. The

</td> </tr>  
<tr>  
<td>

</td>  
<td>

candidates in both datasets were suggested and ranked by English speakers from
the U.S.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

93.9 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_http://ghpaetzold.github.io/data/BenchLS.zip_

Zenodo -  _https://zenodo.org/record/2552393#.XFmRo1xKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_EN_SIMPA

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

A corpus with 1,100 original and manually simplified sentence pairs using data
extracted from SCC websites. There are two simplification versions of the
corpus: lexically simplified only and lexically and syntactically simplified.
For the lexically simplified version, 3,300 sentences were manually simplified
by fluent speakers of English. From these 3,300 sentences, 1,100 were then
selected for the syntactic simplification. Therefore, SimPA has 1,100
sentences that are lexically and syntactically simplified.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

USFD

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

397.1 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_https://github.com/SIMPATICOProject/simpa_

Zenodo -  _https://zenodo.org/record/2551297#.XFmRxFxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_IT_SIMPITIKI

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Italian corpus of complex-simple sentence pairs from Wikipedia and in the
administrative domain (1,166 sentences in total). Each simplification type is
also manually annotated.

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

FBK

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Project specific (XML-based)

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

XML

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

910 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

_https://github.com/dhfbk/simpitiki_ _,_

Zenodo -  _https://zenodo.org/record/2535632#.XFmR9VxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_LEX_IT-BENCHMARK

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Manually created benchmark to evaluate the performance of Italian lexical
simplification systems. It contains 901 pairs of complex sentences and their
simplified version at the lexical level (i.e. replacement of a difficult term
or phrase with a simpler synonym).

</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

FBK

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

None, plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

300 kB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2547994#.XFmR71xKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dataset ID**

</th>  
<th>

SIMPATICO_SIMPLE_MONOLINGUAL

</th> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Repository of 500,000 Italian sentences extracted from the Paisà corpus
(https://www.corpusitaliano.it/) showing high readability according to four
parameters: sentence length, token length, depth of parse tree and verb
“arity”.  
</td> </tr>  
<tr>  
<td>

**Data manager**

</td>  
<td>

FBK

</td> </tr>  
<tr>  
<td>

**Data standard**

</td>  
<td>

Plain text

</td> </tr>  
<tr>  
<td>

**Metadata standard**

</td>  
<td>

None

</td> </tr>  
<tr>  
<td>

**Volume**

</td>  
<td>

27 MB

</td> </tr>  
<tr>  
<td>

**Sharing level**

</td>  
<td>

Open

</td> </tr>  
<tr>  
<td>

**Sharing medium**

</td>  
<td>

OpenAIRE

</td> </tr>  
<tr>  
<td>

**Preservation duration**

</td>  
<td>

Beyond project duration

</td> </tr>  
<tr>  
<td>

**Preservation medium**

</td>  
<td>

Zenodo -  _https://zenodo.org/record/2548585#.XFmSHVxKhaQ_

</td> </tr>  
<tr>  
<td>

**Preservation costs**

</td>  
<td>

No additional cost

</td> </tr> </table>

##  2.5. Open scientific publications

  * Tonelli Sara, Palmero Aprosio, Alessio, & Mazzon Marco. (2019). The impact of phrases on Italian lexical simplification (Version 2.0). Zenodo  . _http://doi.org/10.5281/zenodo.2534080_

  

  * Tonelli Sara, Palmero Aprosio, Alessio, & Saltori Francesca. (2019). SIMPITIKI: A Simplification Corpus for Italian (Version 2.). Zenodo.  _http://doi.org/10.5281/zenodo.2534132_

  

  * Cartelli Vincenzo, Di Modica Giuseppe, Tomarchio, Orazio, López-de-Ipiña Diego, Zabaleta Koldo, & Sanz Enrique. (2018). Citizenpedia: simplifying citizens interaction with public administration. In Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age (p. 106). ACM. Zenodo.  _https://zenodo.org/record/2535208_

  

  * Zabaleta Koldo, López-de-Ipiña Diego, Sanz Enrique, Irizar-Arrieta A, Cartelli Vincenzo, Di Modica Giuseppe, & Tomarchio Orazio (2018). Human Computation to Enhance E-Service 

  

Consumption among Elderlies. In _Multidisciplinary Digital Publishing
Institute Proceedings_ (Vol. 2, No. 19, p. 1221). Zenodo.
_https://zenodo.org/record/2203659_

  * Alessio Palmero Aprosio, & Giovanni Moretti. (2018). Tint 2.0: an All-inclusive Suite for NLP in Italian. _Proceedings of CLIC-it 2018_ . Zenodo.  _http://doi.org/10.5281/zenodo.1565256_

  

  * Palmero Aprosio Alessio, Menini Stefano, Tonelli Sara, Ducceschi Luca, & Herzog Leonardo. (2018). Towards Personalised Simplification based on L2 Learners' Native Language. _Proceedings of CLIC-it 2018_ . Zenodo.  _http://doi.org/10.5281/zenodo.1565296_

  

  * Carolina Scarton, Gustavo Henrique Paetzold, & Lucia Specia. (2018). Text Simplification from Professionally Produced Corpora. _Proceedings of the Eleventh International Conference on_

  

_Language Resources and Evaluation (LREC-2018)_ . Zenodo.
_http://doi.org/10.5281/zenodo.1410451_

  * Carolina Scarton, & Lucia Specia. (2018). Learning Simplifications for Specific Target Audiences. _Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics_ (Vol. 2, pp. 712-718). Zenodo.  _http://doi.org/10.5281/zenodo.1410314_

  

  * Carolina Scarton, Gustavo Henrique Paetzold, & Lucia Specia. (2018). SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain. _Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018)_ . Zenodo.  _http://doi.org/10.5281/zenodo.1410455_

  

  * Carolina Scarton, Lucia Specia, Alessio Palmero Aprosio, Sara Tonelli, & Tamara Martín 

  

Wanton. (2017). MUSST: A Multilingual Syntactic Simplification Tool.
_Proceedings of the_

_IJCNLP 2017, System Demonstrations_ , 25-28. Zenodo.
_http://doi.org/10.5281/zenodo.1042492_

  * Pretel Ivan, Lopez-Novoa Unai, Sanz-Yagüe Enrique, López-de-Ipiña Diego, Cartelli, Vincenzo, Di Modica Giuseppe, & Tomarchio Orazio (2017). Citizenpedia: A human computation framework for the e-government domain. In _2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) _ (pp. 1-6). IEEE. Zenodo.  _https://zenodo.org/record/2415711_

  

  * Zampieri Marcos, Malmasi Shervin, Paetzold Gustavo Henrique, & Specia Lucia. (2017). Complex Word Identification: Challenges in Data Annotation and System Performance. _arXiv preprint arXiv:1710.04989_ .. Zenodo.  _http://doi.org/10.5281/zenodo.1040837_

  

  * Paetzold Gustavo Henrique, & Specia Lucia. (2017). Lexical Simplification with Neural Ranking. _Proceedings of the 15th Conference of the European Chapter of the Association for_

  

_Computational Linguistics_ (Vol. 2, pp. 34-40). Zenodo.
_http://doi.org/10.5281/zenodo.1040785_

  * Paetzold Gustavo Henrique, Alva-Manchego Fernando, & Specia Lucia. (2017). MASSAlign: Alignment and Annotation of Comparable Documents. _Proceedings of the IJCNLP 2017, System Demonstrations_ , 1-4. Zenodo.  _http://doi.org/10.5281/zenodo.1040791_

  

  * Fernando Alva-Manchego Joachim Bingel, Gustavo Henrique Paetzold, Carolina Scarton, & Lucia Specia. (2017). Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs. _Proceedings of the Eighth International Joint Conference on Natural Language Processing_ (Vol. 1, pp. 295-305) Zenodo.  _http://doi.org/10.5281/zenodo.1042505_

  

  * Corcoglioniti Francesco, Palmero Aprosio, Alessio, Nechaev Yaroslav, & Giuliano Claudio. (2016). MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts. _CLiC-it/EVALITA_ . _2016_ . Zenodo.  _http://doi.org/10.5281/zenodo.1048868_

  

  * Paetzold Gustavo Henrique, & Specia Lucia. (2016). Anita: An Intelligent Text Adaptation Tool. 

  

Zenodo. _Computational Linguistics: Technical Papers_ .
_http://doi.org/10.5281/zenodo.1040774_

  * Paetzold Gustavo Henrique. (2016). Understanding the Lexical Simplification Needs of NonNative Speakers of English. _Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers_ (pp. 717-727). Zenodo.  _http://doi.org/10.5281/zenodo.1040782_

  

  * Paetzold Gustavo Henrique, & Specia Lucia. (2016). Collecting and Exploring Everyday Language for Predicting Psycholinguistic Properties of Words. _Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers_ (pp. 1669- 

  

1679). Zenodo.  _http://doi.org/10.5281/zenodo.1040776_

#  3\. SIMPATICO security protection strategy

This final section is dedicated to the **SIMPATICO security protection
strategy** and has been developed as the project progressed. It reflects the
current status within the Consortium about the security of data that has beeen
collected and produced. In the SIMPATICO project **we did not perform
activities, neither produce results, raising any large scale security issues**
. The project does not have the potential for military applications, and also
does not involve the use of elements that may cause any harm to humans,
animals, plants or environment. However, the process of collecting,
processing, storing data might hide some pitfalls. To reduce the **risk of
potential malevolent, criminal and/or terrorist abuse** , which might have
been perpetrated also by malicious people authorized to access the
information, the SIMPATICO Consortium carried out a **twofold security
protection strategy** :

  1. by ensuring that the employed **security layers and privacy-preserving measures** worked properly, keeping access logs and following best practices for system administration; 

  

  2. by employing techniques to prevent information leakage “on-the-fly”, i.e., through the adoption of the **aggregation and** **pseudonymization approach** of personal and sensitive information at collection, communication, and storage time (e.g. via an encryption scheme, hash functions, and/or tokenization). Such an approach neutralised eavesdropping and/or similarly dangerous hack attempts in the unlikely event of successful retrieval, since it secured data, making them completely meaningless to the possible attacker. 

  

  

##  3.1. Authentication, authorization, and encryption

State-of-the-art mechanisms for **authentication, authorization, and
encryption** have been exploited in the implemented processes (concerning data
collection, storage, protection, retention and destruction), so to ensure the
satisfaction of core security and data protection requirements, namely
**confidentiality, integrity, and availability** . In context of SIMPATICO,
the crucial legal challenges are primarily the security measures concerning
authentication and authorization issues. Pursue to the **Directive 95/46/EC**
at the beginning of the project and to the **GDPR** in the second half of
SIMPATICO, the implementation of both computerized authentication and
procedures for managing authorization credentials is required. To assure the
security of and the trust in the system, it is fundamental to provide
technical solutions aimed at allowing the **circulation of digital
identities** and the **access to the e-services** . For identity management
and data protection mechanisms, SIMPATICO follows the standard practice in the
security research community. Please see subsection 5.3 and Annex 3 of the
final deliverable **“D1.5 – Ethics compliance report”** on the so-called
**"SIMPATICO GDPR Self-Assessment"** to better understand the security
measures adopted within the three project pilots in Italy, Spain and the
United Kingdom.

**Identity management** deals with identifying individuals (
**authentication** ) and controlling access ( **authorization** ) to resources
in a system. All the Privacy Enhancing Technologies associated with identity
management aim at identity verification with minimum identity disclosure, and
protection against identity theft. Due to internetworked services and in
general to Cloud technology, the need of a secure identities management has
grown increasingly. Identity and access management (IAM) is the security and
business discipline that “enables the right individuals to access the right
resources at the right times and for the right reasons”. It addresses the need
to ensure appropriate access to resources across increasingly heterogeneous
technology environments and to meet increasingly rigorous compliance
requirements. Technologies, services and terms related to identity management
have been exploited including  Directory services,  Digital Cards,  Service
Providers,  Identity Providers,  Digital  Password Managers,  Single Sign-on,
JSON Web Token and JSON Web Key from OpenID Connect’s model,  OpenID  Connect
,  OAuth  and  XACML.  In particular SIMPATICO’s solutions for IAM are
influenced by many existing and upcoming standards: OAuth 2.0, User Managed
Access (UMA) and OpenID Connect as well as the upcoming Minimum Viable Consent
Record (MVCR) specification from Kantara Initiative.

More specifically, following the “ **Privacy by default and by design** ”
principles and the **GDPR** prescriptions, the SIMPATICO platform adopted an
integrated and multilevel approach to protect the user information from the
fraudulent access and consumption. This has been achieved using a dedicated
Authentication and Authorization Control component (AAC). As for the identity
management, the AAC component has been made compatible with the state of art
identity provisioning technologies (including OpenID Connect, Shibboleth,
SAML, OAuth2.0). This has allowed for integration of the SIMPATICO platform
with the identity provisioning solutions adopted locally by the pilots in a
federated ecosystem. In this integration, AAC has been configured in a way to
obtain minimal amount of personal information necessary to unambiguously and
uniquely identify the user. Note that this data has not been used by the
platform components directly to refer to the user. Instead, those components
use a generated identifier that has been provided by AAC. Such an approach
simplified the realization of the **“right to be forgotten”** policy, as it is
sufficient to remove the association of the user personal data and the user
identifier to make anonymous the data stored in different components of the
platform and associated to the user.

In order to ensure the **data consumption** is performed only by authorized
applications and users, AAC exploited the open standard for authorization,
namely OAuth2.0 protocol. This protocol not only ensures the exchange of
personal data in a trusted context, but also enables controlled access to the
platform services and APIs. In that context, AAC operates as the OAuth2.0
**Authorization Server** for the platform components that expose various APIs
and resources over the network. Furthermore, in order to allow the secure
transmission of personal data, the SIMPATICO APIs supports the HTTPS
communication protocol. The input and output data are transmitted as “plain
text” over HTTPS and encrypted by the TSL (Transfer Security Layer), or by the
SSL (Security Socket Layer). HTTPS is based over certificates and ensure the
client and server mutual authentication.

For the **CDV** component of SIMPATICO, which is the main storage of personal
data in the project, particular attention is dedicate to reduce the **server
side vulnerabilities,** applying all the best **security practices and
policies** about the configuration of the user privileges, remote access and
connections. In order to get the database unreadable by unauthorized
users/applications, the CDV architecture includes a module named Data Security
Manager (DSM) that, implementing the Transparent Data Encryption (TDE)
approach, enables the encryption/decryption of the CDV data in transparent way
from users and application point of view. In order to distribute the security
knowledge about the encryption keys and increase the data security, the CDV
keys and encrypted data have been periodically backuped and stored in
different places. According to the best practice and the architectural
solution adopted by the most important DBMS, see Oracle  5  and Microsoft SQL
Server  6  , the CDV TDE implementation is based on the following concepts:

  * **Master Key** : a key adopted to encrypt the Keys Table. It has been stored into a read only file in the filesystem and access restricted exclusively to each single user registered in the CDV. 

  

  * **User Key** : a key associated to a single CDV user. 

  

  * **Keys Table** : a table to store the User Keys. It has been located in a different server than the Master Key and the Personal Data Table one. 

  

  * **Encryption Key** : a key generated using the Master Key and the User Key. 

  

  * **AES Cipher Algorithm** : the CDV adopts the Advanced Encryption Standard (AES) at 192 bit, defined in the Federal Information Processing (FIPS) standard no. 197  7  8  . 

  

  * **Personal Data Table** : it contains the personal data encrypted/decrypted applying the AES and the Encryption Key. 

  

##  3.2. Focus on data aggregation and pseudonymization techniques

Personal and sensitive data has been and will be made publicly available only
after an **informed consent** has been collected and **suitable aggregation
and/or pseudonymization techniques** have been applied. Before starting the
project activities that require user involvement, a careful investigation on
privacy and security issues has been undertaken, covering in particular the
**Italian, Spanish and UK privacy laws** and the **GDPR** prescriptions,
according to the procedures stated in deliverable **“D1.5 – Ethics compliance
report”** . In this Data Management Plan, data pseudonymization and
aggregation techniques have been identified and applied to personal/sensitive
data before their public release.

As regards aggregation techniques, data confidentiality, integrity and privacy
have been assured **when collecting and processing data** . The information
for each person contained in the release cannot be distinguished from a given
number of other individuals whose information also appear in the release.
Moreover, the pseudonymization of data is another method of ensuring
confidentiality, according to **the Article 29 Working Party Opinion on
Anonymization Techniques** and in relation to the **GDPR** [13]. Where data
are particularly sensitive (e.g. data using detailed personal narratives) then
risks to confidentiality increase. In this case, participants have been
carefully informed of the nature of the possible risks. This does not preclude
the responsibility of the applicant to ensure that maximal pseudonymization
procedures are implemented. A detailed description of the measures that have
been implemented to prevent improper use, improper data disclosure scenarios
and ‘mission creep’ (i.e., unforeseen usage of data by any third party),
within the above-mentioned security protection strategy, have been provided
before the commencement of validation activities.

**The optimal solution has been decided by using a** **combination of
different techniques** , while taking into account the practical
recommendations developed in the above-mentioned **Article 29 Working Party
Opinion on Anonymization Techniques** . Pseudonymization approaches reduces
the linkability of a dataset with the original identity of a data subject, and
is accordingly a useful security measure. These techniques have to adhere
certain requirements to comply with data protection and privacyrelated
legislation in the EU [14]. The following set of requirements (among others)
has been initially extracted from the Directive 95/46/EC and the Article 29
Working Party Opinion on Anonymization Techniques and then updated according
to the GDPR (see Article 32 GDPR “Security of Processing” and related
prescriptions). These are the general guidelines for the SIMPATICO security
protection strategy [13] [15]:

  * **User authentication:** the system has to provide adequate mechanisms for user authentication. 

  

  * **Limited access:** the system must ensure that data is only provided to authenticated and authorized persons. 

  

  * **Protection against unauthorized and authorized access:** the records of an individual have to be protected against unauthorized access. 

  

  * **Notice about use of data:** the users should be informed about any access to their records. 

  

  * **Access and copy users’ own data:** the system has to provide mechanisms to access and copy the users’ own data. 

  

  * **Fall-back mechanism:** the system should provide mechanisms to back up and restore the security token used for pseudonymization. 

  

  * **Unobservability:** pseudonymized data should not be observable and linkable to a specific individual in the system. 

  

  * **Secondary use:** the system should provide a mechanism to export pseudonymized data for secondary use and a possibility to notify the owner of the exported data. 

  

  * **Modification of the database:** if an attacker breaks into the system, the system must detect modifications and inform the system administrator about this attack. 

  

The above-mentioned potential “unforeseen usage” implications of this project
have been examined by the SIMPATICO Ethics Advisory Board and analysed during
the “SIMPATICO GDPR SelfAssessment” (see the final version of “D1.5 – Ethics
compliance report”).

##  3.3. Internal threats and human errors

Most organisations focus on data management risk from external threat but most
breeches occur from internal vulnerabilities. These can be thought of as part
of the same risk continuum. This section looks at internal vulnerabilities and
how to reduce them. There are two main types of internal threats.

  * Security may fall victim to **human error** . For example, an employee may copy information from an entire database table into an email for troubleshooting purposes and accidentally include external email addresses in the recipient list. 

  

  * **Internal Attacks** . While internal accidents often compromise databases, wilful attackers on the inside commit a large portion of database breeches. Many are disgruntled employees who use their privileged access to damage. 

  

Most of these attacks came using the numerous outlets for data on the modern
PC, including USB and Firewire ports, CD and DVD recorders and even built-in
storage media slots. Combined with the fact that storage space on portable
devices has rapidly increased, business professionals can now use personal
storage devices, such as USB memory sticks, digital cameras and smart phones,
to remove or copy sensitive information either for malicious intent or
personal gain.

**Internal threat prevention**

The implementation of a strong and flexible security policy is essential for
SIMPATICO. The security policy provides rules and permissions that are
understandable to both the employee of SIMPATICO partner organizations and
those implementing them so that personal data is prevented from leaving the
office. SIMPATICO policy is based on the security policies in the EU, which
are often enough if enforced to prevent such breeches, and are summarized in
the following **5 points methodology** :  
  
<table>  
<tr>  
<th>

1

</th>  
<th>

Data Protection Policies

</th>  
<th>

Using EU, national and/or local legal guidelines for data protection and
privacy policies (DP)

</th> </tr>  
<tr>  
<td>

2

</td>  
<td>

Internal data protection policies

</td>  
<td>

Written policies and procedures for all staff to sign in and agree to

</td> </tr>  
<tr>  
<td>

3

</td>  
<td>

Clear staff role definition and responsibilities

</td>  
<td>

Staff training, awareness and clear roles and staff responsibilities on data
for access to data with checklists (see attached)

</td> </tr>  
<tr>  
<td>

4

</td>  
<td>

Access control

</td>  
<td>

Managing change in staff and have leave processes in place

</td> </tr>  
<tr>  
<td>

5

</td>  
<td>

Sanctions and audits

</td>  
<td>

Disciplinary action for breach of DP and process guidelines by staff and
threat of audits

</td> </tr> </table>