1\. Executive Summary  8

2\. Introduction  8

2.1. Structure of the document  8

2.2. Relation to other deliverables  9

3\. Data Summary  9

3.1. What is the purpose of the data collection/generation and its relation to
the objectives of the project?  9

3.1.1. Research data supports evaluation and dissemination activities  10

3.1.2. Data in the O4C platform is available for use in hackathons and reuse
beyond these events  10

3.2. What types and formats of data will the project generate/collect?  11

3.2.1. Research data  11

3.2.2. Data in the O4C platform  11

3.3. Will you re-use any existing data and how?  11

3.4. What is the origin of the data?  11

3.5. What is the expected size of the data?  12

3.6. To whom might it be useful ('data utility’)  12

4\. FAIR Data  13

4.1. Making data findable including provisions for metadata 4.1.1. Are the
data produced and/or used in the project discoverable with metadata,  14

identifiable and locatable by means of a standard identification mechanism
(e.g. persistent and unique identifiers such as Digital Object Identifiers)?
14

4.2. Making data openly accessible  14

4.2.1. Which data produced and/or used in the project will be made openly
available as the default?  14

4.2.2. How will the data be made accessible (e.g. by deposition in a
repository)?  14

4.2.3. What methods or software tools are needed to access the data?  15

4.3. Making data interoperable  15

4.3.1. Are the data produced in the project interoperable?  15

4.3.2. What data and metadata vocabularies, standards or methodologies will
you follow to make your data interoperable?  15

4.4. Increase data re-use (through clarifying licences)  15

4.4.1. How will the data be licensed to permit the widest re-use possible?  15

4.4.2. When will the data be made available for re-use?  15

4.4.3. Are the data produced and/or used in the project useable by third
parties, in particular after the end of the project? If the re-use of some
data is restricted, explain why  15

4.4.4. How long is it intended that the data remains re-usable?  16

4.4.5. Are data quality assurance processes described?  16

5\. Allocation of Resources  16

5.1. What are the costs for making data FAIR in your project?  16

5.2. How will these be covered?  16

5.3. Who will be responsible for data management in your project?  17

5.4. Are the resources for long term preservation discussed (costs and
potential value, who decides and how what data will be kept and for how long)?
17

6\. Data Security  17

6.1. What provisions are in place for data security (including data recovery
as well as secure storage and transfer of sensitive data)?  17

6.2. Is the data safely stored in certified repositories for long term
preservation and curation?18

7\. Ethical Aspects  18

7.1. Are there any ethical or legal issues that can have an impact on data
sharing?  18

7.2. Is informed consent for data sharing and long term preservation included
in questionnaires dealing with personal data?  19

8\. References  21

#  1\. Executive Summary

This midterm document – deliverable D4.6 Data Management Plan (M17) –
describes how the research data will be collected and generated throughout the
project and how it will be handled during and after the Open4Citizens project.
It describes the standards and methodologies used for data collection and
elaborates on how the data will be shared and preserved. It also covers the
data that is handled in the Open4Citizens Platform. This midterm version Data
Management Plan is written by following the Guidelines on FAIR Data Management
in Horizon 2020 v3.0, 26 July 2016 provided by the EU Commission. A third and
final version of the DMP is contractually bound to appear by M30 and will
include the final and updated plans for data management in the project.

#  2\. Introduction

This deliverable is the updated and second version of the Data Management Plan
(DMP). By answering the questions outlined in the updated version 3.0
Guidelines on Data Management in Horizon 2020 July 2016 it describes:

  * the handling of research data during and after the end of the project 

  

  * what data will be collected, processed and/or generated 

  

  * which methodology and standards will be applied 

  

  * whether data will be shared/made open access and 

  

  * how data will be curated and preserved (including after the end of the project) (Guidelines on Data Management in Horizon 2020, version 3.0) 

  

The first version of the DMP (M6) followed the ‘Guidelines on Data Management
in Horizon 2020, version 2.0, July 2015 and focused mainly on the categories
of data sets that would be generated and used during the two hackathon cycles.
This second version has a shifted focus to include the research data that is
generated throughout the project and answers to how the project will make the
research data FAIR (Findable, Accessible, Interoperable and Reusable)
(Guidelines on Data Management in Horizon 2020, version 3.0). Since the
Open4Citizens (O4C) Platform also setup to handle data the document also
covers the data that is related to the O4C Platform where applicable. A third
and final version of the DMP is contractually bound to appear by M30 and will
include the final and updated plans for data management in the project.

##  2.1. Structure of the document

The document is based on the template H2020 Programme Guidelines on FAIR Data
Management in Horizon 2020 version 3.0, 26 July 2016 and is structured after
the questions presented in the template. Section 3-6 focuses primarily on how
the research data is managed throughout the project, while section 7-9 also
includes questions that are relevant for the data in the O4C platform. Thus -
where relevant - the sections will cover both topics.

##  2.2. Relation to other deliverables

The datasets that were used in the first round of hackathons are presented in
detail in deliverable D3.2 ‘Data Mapping and Integration’ (delivered in M15).
The more specific details about the hackathons; their themes, associated
challenges, pre-hack activities and key actors are described in detail in
deliverable D3.4 ‘First Hackathon Report’ (M17) whereas the datasets that will
be identified in the upcoming second round of hackathons will be included in
D3.3 ‘Data Mapping and Integration’ (final version M26).

#  3\. Data Summary

##  3.1. What is the purpose of the data collection/generation and its
relation to the objectives of the project?

There are two main groups of data in this project:

  1. the research data that is generated throughout the project and 

  

  2. the data that is uploaded to and handled in the Open4Citizens (O4C) platform. 

  

  

The data that the platform will handle is in the form of datasets generated
from Open Data and authorization data for user logins.

Data collected for and generated in the O4C platform ensures that there is
sufficient and appropriate open data to support the activities related to the
project’s objectives listed in the table below. In the first year, this
especially relates to objective 2 - Exploring hackathons and objective 3 -
Overcoming citizens’ cognitive gap regarding Open Data. In the second year of
the project, the second cycle of hackathons in the five pilot locations, O4C
platform data will additionally be used and generated in the development of
OpenDataLabs (objectives 1, 3, 4, 5 and 6).

The research data generated and collected in the project during the first year
of activity relates especially to formative evaluation of objectives 2 and 3.
In the second year of the project research data collected will support both
formative evaluation related to the development of OpenDataLabs (objectives 1,
3, 4, 5 and 6) as well as summative evaluation elements, regarding the
project’s achievements over all.  
  
<table>  
<tr>  
<th>

**Number**

</th>  
<th>

**Objective**

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

1

</td>  
<td>

Creating OpenDataLabs where citizens can design new services, or improving the
existing ones, in a collaborative environment, and by using open data.

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

2

</td>  
<td>

Exploring hackathons as new forms of collaboration among citizens, technical
experts and public institutions that enable citizens, interest groups and
grassroots communities to understand and use the potential of open data.

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

3

</th>  
<th>

Overcoming the cognitive gap citizens have with respect to Open Data by making
that knowledge available in form of consultants in the OpenDataLabs where
citizens will experience the practical value of Open Data in the conception,
modification, adaptation and maintenance of urban services.

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

4

</td>  
<td>

Combining two specific models of OpenDataLabs, specifically the solutions
development lab and the incubator models.

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

5

</td>  
<td>

Exploring and driving opportunities for further exploitation and
implementation of the developed and tested solutions through social network.

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

6

</td>  
<td>

Creating an international network of cities and organisations where the Open
Data Labs model implemented by Open4Citizens can be replicated and transferred
so generating an international movement based on network cooperation and
learning.

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

**Table 1: Open4Citizens objectives, as stated in the project’s Description of
Action (pg. 2)**

###  3.1.1.  Research data supports evaluation and dissemination activities

Research data in the Open4Citizens project is primarily generated by the
members of the five pilots to support formative and summative evaluation of
the extent to which we are achieving the project’s stated aims. Most of the
data collected for evaluation purposes is focused on the hackathon pressure-
cooker event, held over the course of a weekend in most pilots. Data
collection is carried out consistently across the pilots using standardised
data collection templates consisting of PowerPoint slides. Further data is
generated in line with the evaluation framework described in deliverable D4.1
‘Evaluation Framework’ to support reflections on individual pilots’
contributions and the overarching Open4Citizens project’s contributions to
achieving its objectives. In addition, some of this material is used for
pilot-specific and project-level dissemination activities.

###  3.1.2. Data in the O4C platform is available for use in hackathons and
reuse beyond these events

The purpose of generating and uploading datasets to the O4C Platform is to
make it possible for participants, curious citizens and other interested
stakeholders to locate and find the data that has been produced from the
activities in the emerging OpenDataLabs.

In general ‘Open Data’ means that the data is publically available and can be
used, modified, and shared freely by anyone for any purpose
(http://opendefinition.org/). These open data have a large potential to
enhance several aspects of human life, including transport, health care,
climate and even human behaviour, if they for instance are implemented in new
applications. The O4C project intends to include citizens as a driver for
innovation in the Open Data arena. However many citizens are not necessarily
able to handle Open Data, or even to imagine what to do with them. To help
closing this gap between users and data, the datasets generated and used in
the Open Data Labs is intended to inspire others to see the potential in open
data.

##  3.2. What types and formats of data will the project generate/collect?

###  3.2.1. Research data

Research data generated throughout the project includes primarily qualitative
material, as well as some quantitative information, e.g. about participants in
the hackathons and partners in the OpenDataLabs. Curated and anonymised
materials will be made publicly available. This includes the following:

  * Data gathering and analysis templates (originally produced in Microsoft PowerPoint format) 

  

  * Templates and guidelines for evaluation data gathering and analysis (originally in Microsoft PowerPoint and Microsoft Word/PDF) 

  

  * Completed templates from each pilot containing evaluation material from hackathons (PowerPoint) 

  

  * Questionnaire responses (originally Microsoft Excel documents) 

  

  * Intermediate evaluation analysis outputs based on data gathered in hackathons (Excel and PDF format) 

  

All hackathon participants sign consent forms, allowing the project to use
audio, video, visual and textual material about them. Aliases are used unless
project participants explicitly wish to be quoted or identified using their
real names.

###  3.2.2. Data in the O4C platform

The datasets that have been chosen for the hackathon cycles and uploaded to
the O4C Platform are in CSV format which allows them to be used with the
various tools on the platform.

##  3.3. Will you re-use any existing data and how?

**Research data** will consist primarily of new qualitative information
generated in the project and will therefore not re-use existing data. Some
quantitative data will also be generated as part of the evaluation data
collected, complementing qualitative data collected about users of the O4C
platform.

The data that is uploaded to the **O4C platform** will reuse existing open
data. In addition, datasets generated through O4C activities are intended to
be available for re-use through the platform.

##  3.4. What is the origin of the data?

The research data is original material and will derive from evaluation and
dissemination-related activities. The material to be shared will be produced
by the Open4Citizens consortium members. The datasets uploaded to the platform
will derive from open data repositories and the internet in general from where
the data is ‘publically available and can be used, modified, and shared freely
by anyone for any purpose’. Certain datasets may be made available by O4C
stakeholders who had not previously made this data available, i.e. generating
new open data for use in project activities and beyond.

##  3.5. What is the expected size of the data?

The total amount of research data to be made available is not yet clear. For
the first hackathon cycle, year one of the project, the total size of
evaluation and dissemination materials varies between the five pilots, from
between about 200MB to 3TB, depending on the amount of media (video and
photos) produced.

The size is not yet known for the data in the platform.

##  3.6. To whom might it be useful ('data utility’)

**Research Data**

We intend to make curated research data from the five pilot projects
available, as well as crosscutting material reflecting on the evaluation of
the project as a whole. This data will be useful for researchers,
practitioners and others wishing to duplicate or adapt the Open4Citizens model
for empowering citizens to make appropriate use of open data for improved
service delivery. The analysis material included in the research data will
highlight the strengths and challenges of the approach, allowing others to
learn from the experiences of the project. The availability of templates and
guidelines used in the project will also allow for better adoption of the
approach by others interested in making open data a common good, whether they
belong to academia, the public sector, the private sector groups or civil
society.

Materials that are specifically intended for use by ordinary citizens working
in the O4C platform or as part of an OpenDataLab will be specifically
highlighted in the platform and the labs to ensure ease of access and
understanding. These materials include the toolkits produced as part of the
project (Preliminary Hackathon Starter Kit and Citizen Data Toolkit), as well
as any additional templates and guidelines to facilitate working with and
understanding open data.

**Data in the O4C Platform**

The O4C platform is focused around helping its users gain understanding of
Open Data as well as aiding the development of new services/improve existing
services during the hackathon cycle. The data in the platform is aimed at
being used as:

  * Components in digital mobile or web applications – a dynamic product to access personally meaningful or context-aware data, such as a weather or route planner app. 

  

  * Elements in concepts - i.e. mock-ups of mobile or web applications. 

  

  * Data examples for the participants to gain a greater understanding of Open Data. 

  

  * Visualisation – a statistical representation of data, such as an infographics or a narrative told as a news article (data journalism). The main objective is to communicate what is otherwise “raw numbers in a table”. 

  

  * Digital service – a product-service system with various touch points ingrained with open data. For example, a service where citizens can report faulty street objects (broken lamppost, etc.) using a smartphone application, and the government is notified about these problems and can fix them. 

  

#  4\. FAIR Data

The O4C project is a grant recipient under Horizon 2020 and is therefore
required to deposit peerreviewed publications into an open access repository.

In addition, we wish to participate in the European Commission’s Open Research
Data (ORD) pilot to the extent that this is feasible and useful. This is in
light of the fact that the bulk of research data produced in the project is
qualitative information that cannot easily be used outside the project given
the need for contextual knowledge for its interpretation. By providing open
access to a curated selection of the research data we intend to give access to
anonymised and consolidated evaluation materials, tools and guidelines
produced as part of the project, and the underlying datasets used to address
challenges in urban services during the Open4Citizens hackathon cycle. This is
beneficial for the public, but also for researchers (www.openaire.eu, 2017a).
Providing Open Access will however not remove the author’s copyright
(www.openaire.eu, 2017a).

**Open Research Data**

It is yet to be decided by the project partners whether we will deposit in an
institutional repository of the research institutions with which we are
affiliated, a subject-based/thematic repository or if we will make use of a
centralised repository, like Zenodo that is hosted by CERN, available to all
and set up by the OpenAIRE project (www.openaire.eu, 2017b). We are likely to
use the latter option to ensure that the data is easier to find than if it is
solely deposited in an institutional repository. In addition, to increase
accessibility and findability, we are likely to make the same research data
available through the institutional repositories of the universities that are
part of the Open4Citizens consortium: Aalborg University, Politecnico di
Milano and Technische Universiteit Delft. This use also depends on the
compatibility of the institutional platforms with the type and size of data to
be uploaded. For example, the Aalborg University Research Portal, VBN (Aalborg
University Research Portal, 2017), while compatible with OpenAire (Open AIRE,
2017c) has not previously been used for the type of research material which we
are producing; video, photos and slides. Aalborg University is a signatory of
the Berlin Declaration on Open Access in the Sciences and Humanities (Berlin
Declaration, 2003), whose principles the Open4Citizens project subscribes to.
Signatories to the declaration aspire to ‘promote the Internet as a functional
instrument for a global scientific knowledge base and human reflection and to
specify measures which research policy makers, research institutions, funding
agencies, libraries, archives and museums need to consider’ (Berlin
Declaration, 2003, pg. 1). Decisions regarding the core platform to be used
and the extent to which partners’ national institutional repositories will be
used will be made in good time to make initial research data available in the
second year of the project (2017) and all relevant research data to be
available by the end of the project (project month 30, June 2018).

**Regarding Open Access Journals**

Where it is not possible to publish final peer-reviewed publications in Open
Access Journals, the project partners aim to make publications available in
institutional open access repositories such as VBN at Aalborg University.
This, however, will depend on the individual journals’ policies regarding open
access.

**Open Access through the OpenDataLabs**

An intended the lasting and living legacy of the Open4Citizens project is the
OpenDataLabs. As we are identifying the business and sustainability plans for
the OpenDataLabs, we will be prioritising openness and co-creation within the
labs as a standard approach across the five pilot locations. In the second
hackathon cycle, in 2017, this will involve identifying which guidelines and
standards for openness are applicable across all pilots and can be adopted as
standard.

**Regarding Data on the O4C platform**

The approach to data storage in the platform is also inspired by the FAIR
principles to make it easier for the participants and other interested
stakeholders to find, access and re-use the datasets and make them
interoperable with other datasets. This will be elaborated in the sections
below.

##  4.1. Making data findable including provisions for metadata 4.1.1. Are the
data produced and/or used in the project discoverable with metadata,

###  identifiable and locatable by means of a standard identification
mechanism (e.g. persistent and unique identifiers such as Digital Object
Identifiers)?

For research data collected and generated in the project, a fit-for-purpose
file naming convention will be developed in accordance with best practice for
qualitative data, such as described by the UK Data Archive (2011). This will
involve identifying the most important metadata related to the various
research outputs. Key information includes content description, date of
creation, version, and pilot location.

To make the datasets in the platform easily findable searchable tags have been
added to the metadata. When uploading the data the creator of the dataset also
have the option to create new tags that corresponds to the contents of the
dataset making it easier for other users to find and reuse the data.

##  4.2. Making data openly accessible

**4.2.1. Which data produced and/or used in the project will be made openly
available as**

###  the default?

Certain pilots use medical data as part of the open data in their hackathons
and OpenDataLabs. This includes the Karlstad and Barcelona pilots. The
consortium partners will be guided by the legal and ethical restrictions that
their partners adhere to, i.e. the data owners, who make relevant open data
available. Restriction regarding data availability will come into play if the
partners of the two pilots deem it necessary.

###  4.2.2. How will the data be made accessible (e.g. by deposition in a
repository)?

The research data will be made accessible through an Open AIRE compatible
repository which has yet to be decided upon.

###  4.2.3. What methods or software tools are needed to access the data?

At present Microsoft Office is used for producing research data. However, the
research data will be made available in the most appropriate open source
formats.

##  4.3. Making data interoperable

###  4.3.1. Are the data produced in the project interoperable?

During the first hackathon cycle, research data, consisting of templates, data
gathered from hackathon participants and analysis of materials has been
produced using Microsoft Office. This includes PowerPoint and Excel-formatted
files in particular. The consortium will explore the best open source software
to use instead of these formats, and will make relevant research data placed
in repositories available in these formats instead.

###  4.3.2. What data and metadata vocabularies, standards or methodologies
will you follow to make your data interoperable?

Depending on the choice of repositories we are however likely to follow the
standard of The Data Catalog Vocabulary (DCAT) (Data Catalog Vocabulary, 2014)
as it defines a standard way to publish machine-readable metadata about a
dataset where appropriate. We also intend to use common ontologies and
vocabularies for data.

##  4.4. Increase data re-use (through clarifying licences)

###  4.4.1. How will the data be licensed to permit the widest re-use
possible?

The Open4Citizens project aims to be as open as possible. We take the
guidelines developed by Open Knowledge as our starting point. Specifically, we
will explore the applicability of the Open Data

Commons Open Database License (ODbL) for data created in the project. A
project partner in Milan, OnData (http://ondata.it/), is currently developing
openness guidelines that may be applicable data used and generated in the
Open4Citizens project.

###  4.4.2. When will the data be made available for re-use?

The curated research data related to the first round of hackathons is sought
to be made available by August 2017. By the end of the project in M30 all data
that is not affected by embargo will be made available through the appropriate
repositories.

###  4.4.3. Are the data produced and/or used in the project useable by third
parties, in particular after the end of the project? If the re-use of some
data is restricted, explain why.

The curated research data made available will be available for re-use. However
it may not be feasible for researchers outside the project to interpret and
use any anonymised qualitative research data.

Raw social science research data of this nature generally requires deep
contextual knowledge to be appropriately analysed and interpreted.

The O4C Platform will form a virtual component of the five Open Data Labs. The
aim is that it will be able to exist after the O4C project has been completed.
This means that the Open Data that has been collected, generated and uploaded
to the Platform during the project lifetime will be accessible both after each
hackathon cycle and after the end of the funding period of the O4C project.
The datasets that are uploaded to the O4C platform will be shared through the
website www.opendatalab.eu where everyone will have access to them.

###  4.4.4. How long is it intended that the data remains re-usable?

We will adhere to the repository standard of the chosen repository or
repositories for the project.

###  4.4.5. Are data quality assurance processes described?

The data quality assurance processes are not described yet. These will be
developed based on experiences finding, using and creating open data sets in
the project, including the feasibility of their use in the O4C platform for
creating data-led solutions to service challenges. At the end of the first
hackathon cycle, as this document is being written, a pragmatic approach is
being taken to the quality of the open data being used in the project: at this
stage of the project quality standards are less important than making relevant
data available and using it to the extent possible, thereby learning about
what is needed in order to improve its quality. In further defining the O4C
project's data management plan with respect to research data, we will seek
inspiration in the plans of similar projects and identify good practice
guidelines for social science research data. We will use this input to ensure
that we make good quality research data available.

#  5\. Allocation of Resources

##  5.1. What are the costs for making data FAIR in your project?

Any minor costs for Open Access publishing will be covered by the overall
project dissemination budget. This will be used at the discretion of the
consortium and Aalborg University as the primary investigator. Wherever
possible, free institutional repositories will be used for data and
publications. Expected costs will be further identified in the final version
of the Data Management Plan, based on project needs to the end of the project.

##  5.2. How will these be covered?

There is no significant budget allocation in the project for making the data
FAIR. The project therefore expects to cover costs related to open access to
research data as eligible costs as part of the Horizon 2020 grant (if
compliant with the Grant Agreement conditions). For any additional costs,
sponsorship outside of the project would need to be sought, for example by
partners interested in developing OpenDataLabs or by securing additional
research funding.

##  5.3. Who will be responsible for data management in your project?

Aalborg University (AAU) and Antropologerne (ANTRO) are responsible for the
overall collection and handling of research data while Dataproces is
responsible for the data management of data in the O4C Platform. The pilot
coordinators will be responsible for the collection and handling of research
data in each pilot.

##  5.4. Are the resources for long term preservation discussed (costs and
potential value, who decides and how what data will be kept and for how long)?

This will be further developed as the business cases for the OpenDataLabs are
defined in the project. The consortium expects the main questions relating to
data preservation to be identified and answered as these business cases are
developed.

All datasets that are uploaded to the O4C Platform will be stored on a server
at Dataproces who will ensure preservation and backup throughout the project.
The aim is that the Platform will continue to be available after the O4C
project has been completed. This means that the Open Data that has been
collected, generated and uploaded to the Platform during the project life-time
will be accessible both after each hackathon cycle and after the end of the
funding period of the O4C project. The data in the O4C platform will be
available for as long as the internal server at Dataproces is up and running
and costs covered by the business case by Dataproces.

#  6\. Data Security

##  6.1. What provisions are in place for data security (including data
recovery as well as secure storage and transfer of sensitive data)?

Research data is shared between project partners and stored in collaborative
online working platforms during the project’s lifetime. These are BaseCamp
(https://3.basecamp.com), Google Drive (https://drive.google.com), and Dropbox
(https://www.dropbox.com). Some intermediate and all final versions of
evaluation data collected in the project and analysis outputs of this material
are saved in a standardised filing system with dedicated naming conventions in
the project’s BaseCamp account.

Uncurated and unanalysed material created during the project is stored locally
by the Open4Ctiizens partners according to their institutional data management
and storage guidelines. This locally stored research data includes un-
anonymised questionnaire data from hackathons, as well as consent forms signed
by hackathon and other project participants allowing for the use of personally
identifiable information about them. Consent forms will be kept beyond the end
of the Open4Citizens project. Additional research data such as personal notes,
unused photos and video clips etc. will be safely deleted and discarded after
the end of the project. This research includes all data not made publicly
available for the long term.

In the finished form of the platform the uploaded data is secure and
recoverable with daily backups, where Dataproces can go back to any file from
any day for all 365 days a year. Dataproces also fulfil all data management
comments regarding the European Personal Data Protection Act.

##  6.2. Is the data safely stored in certified repositories for long term
preservation and curation?

At the time of writing this deliverable, the Open4Citizens project partners
are identifying the most appropriate repository or repositories in which to
make research data available for the long term. An update on decisions made
will be provided in the project’s final Data Management Plan, due in M30.

#  7\. Ethical Aspects

##  7.1. Are there any ethical or legal issues that can have an impact on data
sharing?

**User-generated data**

In the second hackathon cycle it is likely that user-generated data will be
increasingly important for developing open-data driven solutions in
Open4Citizens hackathons. Examples include crowdsourced data such as that made
available in platforms like Open Street Map

(www.openstreetmap.org), public social media data, as well data scraped from
service and product review sites. The Open4Citizens consortium intends to
adopt existing standards and approaches regarding the use of this kind of
data. Our primary guide in defining an Open4Citizens guideline to using this
type of data will be the licences and guidelines available through the Open
Data Commons (https://opendatacommons.org) developed by Open Knowledge
International  (https://okfn.org/)  . In essence, the Open Data Commons Open
Database License (OBdL) states that the databases to which it applies allow
users to freely share, create and adapt from the database, as long as public
use is attributed, shared alike and kept open. However, as these guidelines
are voluntary, the consortium intends to engage with members of our advisory
board to determine which current approaches to openness we should adopt. We
intend, for example, to review and appropriately adopt guidelines produced by
the Open Data Institute (https://theodi.org/guides) and Open Knowledge
International, as leaders in the field, as well as any other relevant
guidelines.

We foresee that balancing participants’ rights to the intellectual property
entailed in their hackathon outputs with the desire for openness may be
challenging. We will therefore stay informed about developments in the area of
rights, ethics and openness throughout the life of the project to ensure that
we are transparently applying best practice procedures and guidelines. We
expect that debates regarding use of user-generated data in data journalism
will be one useful source of guidance.

**Data in the O4C platform**

When organising the events Open4Citizens will collect information from public
repositories, which contain Open Data. Since Open Data consist of information
databases that are public domain, the data can be freely used and
redistributed by anyone. Open4Citizens is thus not subject to any regulations
regarding proper data storage, including principles stipulated in The Data
Protection Directive 95/46/ECP and the General Data Protection Regulation (EU)
2016/679.

When providing Open Data for the hackathons and related events, Open4Citizens,
its employees, and any contributing partners of Open4Citizens or its
employees, shall not be liable for any harm arising from the use of the
collected datasets shared through the O4C Platform, including but not limited
to, how participating parties handle and develop the Open Data available on
the O4C Platform.

In regards to the Open Data from various data sources that are made available
on the O4C Platform, Open4Citizens does not guarantee that this data has been
published with the prior, necessary and informed approval that it requires.

##  7.2. Is informed consent for data sharing and long term preservation
included in questionnaires dealing with personal data?

The gathering and analysis of research data in the project is guided by
standard ethics guidelines for the social sciences (e.g. as discussed in
http://ec.europa.eu/research/participants/data/ref/h2020/other/hi/ethics-
guide-ethnoganthrop_en.pdf).

For research data collected in relation to Open4Citizens hackathons, as well
as questionnaires and other personally identifiable information generated,
informed consent is sought. All participants in hackathons are requested to
provide their consent for all data produced to be used by the project. Figure
1 represents the template consent form used for the first hackathon cycle
below. In addition all users of the platform will be asked for consent when
creating a profile in the O4C platform.

**Figure 1: Draft consent form used by all five pilots in the first hackathon
cycle of the O4C project**