#  Executive Summary

The present document is deliverable “D9.7 Data Management Plan” of the Easy
Reading project which is funded by the European Union’s Horizon 2020 Programme
und Grant Agreement #780529.

The purpose of this document is to provide the plan for managing the data
generated and collected during the project. The Data Management Plan (DMP)
describes the data management life cycle for all data sets to be collected,
processed and/or generated by a research project. It covers:

  * The handling of research data during and after the project 

  

  * What data will be collected, processed or generated 

  

  * What methodology and standards will be applied 

  

  * Whether data will be shared/made open and how 

  

  * How data will be curated and preserved 

  

The DMP is currently in an initial state, as the project has just started.
Following the EU’s guidelines regarding the DMP, this document may be updated
- if appropriate - during the project lifetime (in the form of deliverables).

The DMP currently identifies the following data as research data generated
during the project:

  * Structure of the user profile 

  

  * Usage statistics 

  

  * Anonymized user profile data 

  

  * User evaluations 

  

  * Administrative metadata 

  

Most data sets will be provided openly on public web servers, via a REST-API
1  for real time data or other means of provision. As the user profiles may
contain sensitive data even if they are anonymized, it is, at this stage,
currently unclear what will be openly available and what not.
#  Introduction

This document is the Data Management Plan (DMP). The consortium is required to
create the DMP because the Easy Reading project participates in the Open
Research Data pilot. The DMP describes the data management life cycle for all
data sets to be collected, processed and/or generated by a research project.

##  Scope

The present document is the Deliverable 9.7 “D9.7 – Data Management Plan”
(henceforth referred to as D9.7) of the Easy Reading project. The main
objective of D9.7 is to provide the plan for managing the data generated and
collected during the project.

According to the EU’s guidelines regarding the DMP, the document may be
updated - if appropriate - during the project lifetime (in the form of
deliverables).

##  Audience

The intended audience for this document is the Easy Reading consortium and the
European Commission.

#  Data Summary

The Easy Reading framework will improve the cognitive accessibility of
original digital documents by providing real time personalisation through
annotation (using e.g. symbol, pictures, video), adaptation (using e.g.
layout, structure) and translation (using e.g Easy-to-Read, Plain Language,
symbol writing systems). The framework provides these (semi-)automated
services using HCI techniques (e.g. pop-ups/Text-To-Speech (TTS)/captions
through mouse-over or eye-tracking) allowing the user to remain and work
within the original digital document. This fosters independent access and
keeps the user in the inclusive discourse about the original content. Services
adapt to each user through a personal profile (sensor based tracking and
reasoning of e.g. the level of performance, understanding, preferences, mood,
attention, context and the individual learning curve).

During the project, data will be generated to improve the Easy Reading
framework, to model the capabilities and preferences of the user and to
evaluate the success of the project. The purpose of the data
collection/generation can be subdivided into the following points:

  * **Modelling the user:** The model of the user is required as a basis to provide services on top of this information which helps users with cognitive disabilities browsing the web. 

  

  * **Framework performance monitoring and improvement** : Collected data will be used to improve the tool. Evaluations of usage statistics for example will be used to determine which functions were more helpful than others, which configurations were used and on which content areas issues occurred for the user. 

  

  * **Matching services to user needs:** Based on user profile data and usage data, suggestions for services/functions can be made automatically. 

  

  * **Pre-configuration of functions to simplify web content:** Depending on user profile data and usage data, functions can be pre-configured to provide helpful support and a good user experience from the start when installing a new function. 

  

  * **Adjusting functions according to user profile:** Besides the initial configuration of the functions, adjustments and fine-tuning on-the-fly using usage statistics will be possible too. 

  

  * **Learning about the target group:** From a research perspective, major contributions in the field of web accessibility and people with cognitive disabilities can be made by collection and analysis of usage statistics. 

  

  * **Deducing rules for cognitively accessible web content:** Based on these findings, rules for cognitively accessible web content may be deduced and support web developers and content creators to make website easier to understand for everyone. 

  

##  Types and Formats of Data

Currently the following data sets were identified. As mentioned before, these
are subject to changes during the project lifetime.

  * Structure of the user profile: 

    * Cognitive capabilities of a user o Current mood of a user o Level of confusion o Usage statistics o Which target group uses which kinds of services  Accumulated usage statistics o Time of the day o Mood 

  

  

  * Disabilities / CapabilitiesAnonymized user profile data o Function configuration preferences: Describes which configuration of a function the user uses 

    * Time consumption per UI-element: Describes at which elements of the content the user spends most of the time 

  

    * Level of confusion per element: Describes if there are elements of the content which especially confuse the user 

  

    * Understandabilty of elements: Describes which parts of the content the user understands/are easy to interact with, and which are not 

  

  

  * User evaluations: Evaluations will be conducted during the course of the project to to ensure requirements of this manifold user group are considered adequately from the very beginning of the project. These evaluations involve user satisfaction tests to ensure that the user interface as well as the features of the tool meet the actual needs of people with cognitive disabilities. 

  

  * Administrative metadata: When and how data was created e.g. 

  

The main data exchange format for data sets will be JSON, while the data
itself is stored in a relational database. Also other kinds of structured data
will probably be made openly available using a REST-service  2  using JSON  3
as data format. Manually created data, like evaluations or data used in
publications, will be made available as PDFs.

##  Reuse of existing data

At this state of the project, no existing data is planned to be reused. This
might be subject to change during the lifespan of the project.

##  Origins of Data

Most data will be generated and retrieved during the actual usage of the tool,
either by user interaction or by tracking of the user’s actions. In addition,
relevant data will be created due to configuration processes either by the
user or a caregiver. Evaluations will also provide further useful data.

  * Data generated by user interaction: During user interaction, data can and will be collected to achieve the goals mentioned before. Amongst others, the following data may be useful: o The functions the user prefers to use 

    * The way the user uses functions and how the tool and its features are configured o The kind of websites the user visits. This is very sensitive data of course, so some other data might be used instead. For example not the actual website, but measures like the complexity of the website layout or the complexity of the text. 

  

    * The time users spend on website, or parts of a website. Again, this is of course very sensitive data and due to ethical considerations, other measures which reflect the most interesting outcomes will be used instead. 

  

    * Level of confusion of the user 

  

  

  * Tracking of the user with sensors will be possible: 

    * Mouse and keyboard tracking o Head and eye tracking 

  

  

  * Due to client-side configuration of functions, data will also be generated 

  

  * Data will also be generated by carers who can do an initial configuration or users of the target group who can use a wizard independently, which allows to manually add information about capabilities and preferences 

  

  * User evaluations through questionnaires, interviews and other means. 

  

##  Expected Size of the Data

At this state of the project, the expected size of the data is unknown, as the
user profile and its structure is not fully defined and implemented.

##  Data Utility

The data will be useful to the project (consortium), to other research
projects in a similar field which are concerned with people with cognitive
disabilities consuming web content and for companies which want to create
products or content of this kind with people with cognitive disabilities in
mind.

#  FAIR Data

The research data generated by the Easy Reading project should be 'FAIR';
findable, accessible, interoperable and re-usable.

##  Findable Data

  * **Discoverability of data:** Since the user and usage data is stored in a relational database, it can be accessed using SQL queries. The database structure/schema will be made available in some sort of wiki. 

  

  * **Identifiability of data:** Not specified at this stage of the project 

  

  * **Naming conventions:** Most of the data will be stored in a relational database. Therefore standard SQL database naming convention are being used: 

  

o Singular names for tables o Singular names for columns o Schema name for
tables prefix (E.g.: SchemeName.TableName) o Pascal casing (a.k.a. upper camel
case)

  * **Search keywords:** Not specified at this stage of the project 

  

  * **Clear versioning:** Not specified at this stage of the project 

  

  * **Metadata creation standards used:** The use of specific standard for metadata creation is not yet decided upon. 

  

##  Accessible Data

Data generated by the Easy Reading project contains sensitive data. For
example the user profiles themselves, even if they are anonymized, are
considered sensitive. Therefore the consortium is very cautious on making this
data openly accessible. Currently following data might be made openly
available:

  * structure of the user profile 

  

  * user evaluations 

  

  * accumulated usage statistics (in contrast to individual user statistics) 

  

  * deduced data from evaluations as part of publications 

  

At this stage of the project it is not fully decided if individual usage
statistics, anonymized user profile data and administrative metadata will be
made openly accessible due to the sensitive nature of this kind of data.

Openly available data will be made public by following means:

  * Publications (evaluations, accumulated usage statistics) 

  

  * Direct download (user profile structure) 

  

To access openly available data no special software or method will be required
at the current stage. For publications and evaluations, a standard PDF viewer
is sufficient. Usage statistics and the user profile structure can be
displayed using a JSON scheme parser. This data and its associated metadata,
documentation and code are deposited on the project website.

**Data restrictions:** There are no restrictions to openly available data.
Other data is currently only available for consortium members and it needs to
be decided which parts of this data will be made available and in which way.

##  Interoperable Data

Data is structured (relational database, JSON), but due to the highly
sensitive nature of parts of this data, it is not openly available at this
point in time. However, in the future interoperability of less sensitive parts
of the data is easily possible (e.g. parts of usage statistics with REST
service and data exchange format JSON). Data types are not fully decided at
this stage of the project and will evolve over the course of the project, but
standard types will of course be applied as often as possible.

##  Data Reusability

To ensure FAIR use of data and to ensure widest reuse possible, openly
available data generated by the project is planned to be licensed under the
Apache License 2.0. Third parties will be able to use this openly available
data.However, it is at this stage of the project not possible to specify a
date when the data is available for reuse. Neither is it fully decided which
parts of the data will be openly available. For instance, parts of the usage
statistics might be deemed as sensitive data in terms of privacy.

#  Allocation of Resources

Costs for making your data FAIR are covered by the project budget. The project
leader (JKU) coordinates the data management of the project. The costs and
potential value of long term preservation has not yet been determined due to
the early stage of the project. This will be dealt with later on over the
course of the project

#  Data Security

As sensitive data is stored and transferred, data security is of utmost
importance for the Easy Reading project. At the moment, data used by the
framework is stored on cloud server infrastructure from IBM (IBM Bluemix).
Later on in the project this could be moved to Amazon AWS. Both platforms
provide sufficient measures and tools to provide data security. Data will be
stored on Servers in the EU.

  * IBM Bluemix Cloud Security:  _https://console.bluemix.net/docs/security/index.html#security_

  

  * Amazon AWS Cloud Security  _https://aws.amazon.com/security/_

  

Regular backups using cron-jobs of the relational database will ensure easy
data recovery. Data transfer will be exclusively done via HTTPS /WSS (Web
Socket Security).

Ethical Aspects

At the current stage of the project all ethical aspects are covered in section
5 “Ethics and Security” of the Grant Agreement of the project.

#  Conclusions

The purpose of this document is to provide the plan for managing the data
generated and collected during the project; The Data Management Plan.
Specifically, the DMP describes the data management life cycle for all data
sets to be collected, processed and/or generated by a research project. It
covers:

  * the handling of research data during and after the project  what data will be collected, processed or generated.  what methodology and standards will be applied. 

  

  * whether data will be shared/made open and how 

  

Following the EU’s guidelines regarding the DMP, this document may be updated
- if appropriate during the project lifetime (in the form of deliverables).

Due to the sensitive nature of some data collected, it is unclear at this
point of the project if all data will be made openly available. Data sets that
will be openly provided to the public will be hosted on web servers or
provided in real time via REST endpoints. Finally, data sets will be preserved
after the end of the project on the pilot’s web sites, on web servers or other
web-based solutions.