1 Introduction  5

2 Data summary  5

2.1 Administrative information  5

2.2 Purpose of data collation  5

2.3 Type and format of data collated  6

2.4 Re-use of existing data  7

2.5 Expected size of data  7

2.6 Expected data utility  7

3 Preserving access to quantitative WeGovNow platform evaluation data  8

3.1 Making quantitative WeGovNow platform evaluation data findable  8

3.2 Making quantitative WeGovNow platform evaluation data openly accessible  9

3.3 Making quantitative WeGovNow platform data interoperable  9

3.4 Increase re-use of quantitative WeGovNow platform evaluation data  10

4 Allocation of resources  10

5 Data security  10

6 Ethical aspects  11

7 Preserving access to publications  12

#  Introduction

According to available guidance, H2020 projects are to provide a first version
of the Data Management Plan (DMP) within the first six months of the project
1  . The initial DMP should be updated during the project lifetime. The
present document represents a final update of the initial version of the DMP.

The DMP presented throughout this document starts with a summary of the data
collated in the framework of the WeGovNow pilot evaluation (Chapter 2). This
is followed by a description of how access quantitative data collated for the
purposes of formative pilot platform evaluation will be preserved (Chapter 3).
Next, the resources allocated to this are assessed (Chapter 4) and measures
for ensuring data security are described (Chapter 5). This is followed by a
description how ethical aspects and data privacy according to GDPR has been
addressed (Chapter 6). Finally, it is described how access to publications is
preserved (Chapter 7).

#  Data summary

##  Administrative information

Grant Agreement No.: 693514

Acronym: WeGovNow

DPM version: 2.3

Planned update: n. a.

DMP responsible: Lutz Kubitschke

##  Purpose of data collation

The WeGovNow project is to develop a new type of online platform for citizen
engagement, thereby integrating existing software applications and newly
developed ones in accordance with a multi-staged development approach (Figure
1).

_Figure 1 – Multi-staged development approach of the WeGovNow online platform_

Phase I Phase II Phase III Phase IV

**Basic Iterative prototype Platform piloting**

**Platform architecture**

###  component refinement & under day to day development integration extension
conditions

The WeGovNow platform will has been piloted in three municipalities from
project month 25 onwards. During the pilot evaluation phase data have been
gathered in relation to different evaluation objectives, namely whether

  1. the WeGovNow pilot system works as anticipated (viability perspective) 

  

  2. the WeGovNow pilot system is worth being maintained after the ending of the pilot duration (sustainability perspective) 

  

  

Outcomes have been feed into the development of guidance on the further
mainstreaming of the WeGovNow pilot platform after the ending of the pilot
project duration, including recommendations on further exploitation of the
WeGovNow pilot platform as a major project output.

##  Type and format of data collated

Different types of evaluation data have been gathered throughout the project’s
pilot phase, including quantitative data:

  * _Quantitative evaluation data generated by means of automated monitoring of_ _platform usage:_

  

The WeGovNow online platform developed includes different functional software
components which enable the pilot users to post and manipulate different types
of content. This is reflected by the case-based data set including the
following variables:

  * User account created 

  

  * User account automatically validated o User account manual validation requested o User account manually validated o Date of birth of registered user account holder o Sex of registered user account holder 

  

  * No. of original contributions posted through the WeGovNow First Life platform component 

  

  * No. of comments posted through the WeGovNow First Life platform component 

  

  * No. of original contributions posted through the WeGovNow Community 

  

Maps component o No. of original contributions updated through the WeGovNow
Community

Maps component o No. of comments posted through the WeGovNow Community Maps
component

  * No. of objects created through the WeGovNow First Life component o No. of objects updated through the WeGovNow First Life component o No. of objects deleted through the WeGovNow First Life component o No. of votes casted d through the WeGovNow LiquidFeedback component 

  

These data have been processed in a common spread sheet processing programme
format (Microsoft Excel).

  * _Qualitative evaluation data gathered by means of different data gathering methods:_ Semi-structured interviews were conducted with a number of selected stakeholders at the pilot sites for the purposes of the viability assessment, focussing on identifying potential impacts of the pilot service on the various stakeholder groups involved. Outcomes were documented in terms of a common reporting template. Further to this qualitative evaluation data has been gathered by means focus group sessions. In thematic regard, these events focused on gathering the stakeholders’ perceptions of the utility, usability and reliability of the pilot services, including the technical infrastructure through which the pilot services are delivered at each of the pilot sites. Also, perceived impacts have been addressed. Outcomes were again documented in terms of a common reporting template. All reporting templates were processed as a text files with help of common word processing software (MS Word). 

  

##  Re-use of existing data

The WeGovNow project specifically has developed and piloted a new type of
civic engagement platform integrating various participation functions. There
was no existing data available that could be utilised for the purpose of pilot
platform evaluation in the framework of WeGovNow.

##  Expected size of data

The following data volume was generated:

  * _Quantitative data gathered_ : 

  

A case-based variable set was generated for 11.833 instances overall.

  * _Quantitative data gathered:_

  

Overall, 18 aggregated reporting templates have been processed.

##  Expected data utility

Data gathered by means of the project’s multi-method evaluation approach
specifically relate to the utilisation of the newly developed WeGovNow pilot
platform in three participating pilot municipalities. These data are of
utility primarily for formative evaluation purposes to support the further
mainstreaming of the pilot platform, the latter representing a key output of
the project. The pilot platform may however undergo further optimisation prior
to envisaged mainstreaming after the ending of the pilot project. Due to the
formative nature of the evaluation design adopted for the purpose of the
WeGovNow project, the long term value of the evaluation data to be generated
can be assessed as very low. Type and nature of the evaluation data gathered
do not offer opportunities for subsequent research, e.g. in terms of secondary
analyses or replication of results.  2  However, the quantitative data set
that has become available from automated usage monitoring during the overall
project’s pilot phase may potentially be utilised by others for verifying any
published results referring to these data, albeit with a rather low
probability given the strong RTD-focus of the current project.

#  Preserving access to quantitative WeGovNow platform evaluation data

##  Making quantitative WeGovNow platform evaluation data findable

Beyond the project duration, it is planned to make an anonymous case-level
data set from the automated pilot platform usage monitoring available through
the GESIS Datorium repository. The data set consists of 11.833 instances and
11 coded variables. To this end, the data set is intended to be made available
after the formal closing of the project.

The user ID which might in conjunction with registration data stored in the
pilot platform, at least theoretically, enable the identification of an
individual who’s platform usage activities have been monitored is not included
in the quantitative data set that has been generated for formative evaluation
purposes. Also, no person related information stemming from the required
registration of the pilot users to the pilot platform has been derived from
the platform for evaluation purposes. Hence, no personal data or any other
information that would theoretically allow a third party to infer a pilot
user’s identify has been included in the data set generated for formative
evaluation purposes. This ensures anonymity of the data set to be publicly
preserved.

Findability will be supported by relying on the metadata framework applied by
the data sharing repository to be utilized (GESIS Datorium)  3  . In
particular, the following metadata will be provided:

  1. Title 

  

  2. Principle investigator & Institution 

  

  3. Publisher 

  

  4. Publication Year 

  

  5. Availability 

  

  6. Subject Area 

  

  7. Topic Classification 

  

  

In contrast to “replicablility” in this sense, we understand “reproducibility”
as making available data sets to others for verifying published results. C.f.
e.g. Peng, R. (2009): Reproducible research and Biostatistics. In:
Biostatistics, 10 (3): 405-408.

3  This meta data framework is compatible with the codebook standard of the
Data Documentation Initiative (DDI 2). c.f. Wolfgang Zenk-Möltgen and Monika
Linne (2014): Metadatenschema zu datorium - Data

Sharing Repositorium. GESIS-Technical Reports 2014/103

  8. Abstract 

  

  9. Geographical Area 

  

  10. Data collection Mode 

  

  11. Survey Period 

  

  12. Rights 

  

  13. Notes 

  

  14. File description 

  

  15. Research Data Type 

  

  16. Language 

  

  17. Number of Variables 

  

  18. Number of Units 

  

  19. Unit Type 

  

  20. Software 

  

  

These metadata will be fed by means of a persistent digital identifier (DOI)
into the international community of DataCite and thus become findable at an
international level.  3

##  Making quantitative WeGovNow platform evaluation data openly accessible

As mentioned above, an anonymous case-level data set derived by means of
automated pilot platform usage monitoring will be uploaded to the GESIS
Datorium data sharing repository. An account has already been registered.

The data set will be made available in terms of an OpenDocument Spreadsheet
(.ods). In conjunction with the metadata to be provided the data will be
immediately usable with help of commonly available spreadsheet software. No
particular documentation of access software will thus be required.

Access to this data is planned to be provided to everybody. Setting up a Data
Access Comitee, e.g. for concluding particular data access agreements, is
considered not necessary.

##  Making quantitative WeGovNow platform data interoperable

As discussed earlier the type and nature of the data set generated for the
purposes of for formative evaluation of the WeGovNow pilot platform is not
expected to be of high longterm value (c.f. 2.6). When it comes to potentially
re-combinations with different datasets from different origins in particular,
no value is seen at all due to the formative evaluation approach pursued.

As discussed earlier as well, the quantitative data set that has become
available from automated usage monitoring might be utilised by others for
verifying any published results referring to these data, albeit with a rather
low probability given the strong RTD-focus of the current project. This will
be supported by a documentation of the all variables and numeric codes
included in the data set that will be provided on the data sharing repository
(GESIS Datorium). Where possible available standard codes have been followed,
for example in the case of identification of date of birth data were coded
according to ISO 8601\.

##  Increase re-use of quantitative WeGovNow platform evaluation data

The data set includes automatically derived monitoring data on pilot platform
utilization. Prior to further processing, the data derived from the pilot
platform underwent quality assurance procedure in relation to data integrity
in terms of a plausibility assessment.

The data set will be made publicly available on GESIS Datorium following the
closing of the WeGovNow project. No embargo period is foreseen.

No particular restrictions on the re-use of the data are planned to be
imposed. The appropriateness of different licensing agreements under the
Creative Commons licensing framework is currently explored.

The data set will remain re-usable until the repository withdraws or goes out
of business.

#  Allocation of resources

Costs for data preparation and documentation are covered by the project
budget. The costs for data preparation to be FAIR cannot be exactly specified
at the current stage. However, expenses for data set preparation, data
management and additional documentation concerning those data to be made
openly accessible are estimated to not exceed 0.5 person months. No additional
expenses are expected to accrue for purchasing supportive tools, e.g. for
working with DDI, and repository charges for data submission.

The lead partner (empirica) of the project’s evaluation work package (WP4)
takes responsibility for data management. Lutz Kubitschke and Sonja Müller are
responsible for data storage, archiving and publication.

#  Data security

During the project, all evaluation data has been stored at the server of the
lead organization (empirica) responsible for the evaluation work package
(WP4), with daily backup at an institutional off-site server. The team member
responsible for storage is supported by empirica’s IT team. Back up are
checked manually at two weeks intervals. No additional costs are accruing for
storage and back-up.

When it comes to quantitative monitoring data, sensitive data (the user
account ID recorded by the pilot platform) has been separated to create an
anonymised data set. Beyond the user ID , no data item processed and stored is
assessed as sensitive.

When it comes to qualitative evaluation data generated for evaluation
purposes, this data is planned to be stored locally at empirica’s servers for
10 years, whereby no costs will be associated with local storage. As described
above, qualitative raw data will not be made available to external parties
preventing data privacy threats. Only to project members will be granted
access on request, with clearance of a non-disclosure agreement.

#  Ethical aspects

Informed consent for the sharing of anonymised evaluation data and long term
preservation was included during data collation. Sensitive data was separated
and kept secure.

When it comes to the processing of personal data in the framework of the local
validation trials which have been implemented in the three WeGovNow pilot
municipalities GDPR compliance was ensured. During the overall project’s pilot
phase, the WeGovNow platform has been operated by three municipalities under
day-to-day, namely in Turin, in the London Borough of Southward and in San
Doná di Piave. With help of the platform, each pilot municipality offered a
publicly available pilot service to its citizens until the end of the formal
project duration. In technological respect, the individual platform components
(software applications) were hosted by different consortium members according
to a Software-as-aService (SaaS) deployment model. Pilot users entered data
into the pilot platform through a common web interface. User data were shared
across the platform components, either directly between individual components
or by means of a common logger data base.

From a legal point of view, two different perspectives deserved attention in
framework of the WeGovNow pilots when it comes to GDPR requirements, namely an
external one and an internal one:

  * External: One the one hand, a legal relationship was established between the pilot service provider (pilot municipality) and the pilot service user (citizen). 

  

  * Internal: On the other hand, a legal relationship was established between the pilot service provider (pilot municipality) and those parties processing data on its behalf in accordance with a SaaS deployment model (technology partners hosting one or more platform component remotely). 

  

As far as the processing of personal data was concerned, the GDPR creates
obligations for the WeGovNow municipalities offering the pilot service (“data
controllers”) to their citizens (“data subjects”) with help of WeGovNow
component providers (“data processors”). These obligations were mat in various
ways:

  * Terms of use statement (ToU) complying with GDPR requirements was developed by each pilot site and made available through the local pilot platform instances to the pilot users. Consent was requested prior to user registration. 

  

  * A data privacy statement was developed by each pilot site and made available through the local platform instances to the pilot users. Consent was requested prior to user registration. In this context, user were informed about which types of personally identifiable information was collected about them across the WeGovNow platform components, how the data is used and how users can control the information that is gathered. Current data protection legislation as well as the new GDPR put an obligation on data controllers to ensure data subjects can rectify remove or block incorrect data about themselves. Users were also informed about their various rights in relation to data protection as stipulated by GDPR. 

  

  * To be able to respond to user request in relation to these rights, it was identified in advance what personal data were held within the individual WeGovNow platform components, where it comes from, who it is shared it with, how its processing can be restricted and how it can be erased. Also, a process was identified din advance how the consortium would react if a pilot user asked to have his/her personal data deleted, for example. In such a case the pilot municipality receiving such a request from one of its citizens was able to rely upon a commonly agreed procedure for informing the partners concerned, monitor how the user claim is met and provide informed feedback on this matter to the pilot user. 

  

  * The GDPR makes privacy by design an explicit legal requirement under the term ‘data protection by design and by default’. As a general rule, personal data was processed within and across the WeGovNow platform software components only for those purposes intended to be achieved by the component. 

  

When it comes to the legal relationship between the pilot municipalities and
the technical partners hosting one or more software components remotely, GDPR
differentiates between the “data controller” (the pilot municipalities) and
the “data processor” (the technical partners). Processing of personal data on
behalf of a data controller requires an assignment in writing between both
parties according to GDPR. Therefore a data processing agreement was concluded
bilaterally between each of the three pilot municipalities and each WeGovNow
component provider prior to the starting of the local pilots. Overall, 12 data
processing agreements were hence concluded.

#  Preserving access to publications

Project partners have relied on research results from WeGovNow for authoring
scientific papers for journals and book chapters, as well as presenting
conference papers in relevant disciplines. To preserve their accessibility
these have been made available on different repositories as follows:

  * The Zenodo open access repository 

  

  * The open access repository of the University of Heidelberg 

  

  * The open access repository of the University of Turin 

  

  * The Liquid Democracy Journal (permanently archived at German National Library) 

  

  * The ACM digital Library 

  

  * IEEE Xplore Digital Library 

  

  * International Conference on Cartography and GIS (ICC&GIS) 

  

**Title**

**)**

**Year**

**(**

**Authors**

**Journal/book/conferen**

**ce**

**Type**

**Link to**

**publication**  
  
<table>  
<tr>  
<th>

**Title (Year)**

</th>  
<th>

**Authors**

</th>  
<th>

**Journal/book/conferen ce**

</th>  
<th>

**Type**

</th>  
<th>

**Link to publication**

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

A Fair Distance Function (2017)

</td>  
<td>

Behrens, J. and B. Swierczek

</td>  
<td>

The Liquid Democracy Journal on electronic participation, collective
moderation, and voting systems

</td>  
<td>

Other

</td>  
<td>

_http://www.liq_ _uid-democracyjournal.org/issu_ _e/5/_

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

LiquidFeeback’s Issue Limiter (2017)

</td>  
<td>

Behrens, J., Nitsche, A. and B. Swierczek

</td>  
<td>

The Liquid Democracy Journal on electronic participation, collective
moderation, and voting systems

</td>  
<td>

Other

</td>  
<td>

_http://www.liq_ _uid-democracyjournal.org/issu_ _e/5/_

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

Unified User

Management with

LiquidFeedback (2018)

</td>  
<td>

Behrens, J. and B. Swierczek

</td>  
<td>

The Liquid Democracy Journal on electronic participation, collective
moderation, and voting systems

</td>  
<td>

Other

</td>  
<td>

_http://www.liq_ _uid-democracyjournal.org/issu_ _e/6/_

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

Data Quality Concept for eGovernment Web-Map

Based Services (2018)

</td>  
<td>

Noskov A., Zipf A. and A.

Rousell

</td>  
<td>

Proceedings 7th

International

Conference on

Cartography and GIS

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://iccgis20_ _18.cartographygis.com/7ICCGI_ _S_Proceedings/_

_7_ICCGIS_2018_

_%20(34).pdf_

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

Computer Vision

Approaches for Big Geo-

Spatial Data: Quality

Assessment of Raster Tiled

Web Maps for Smart City

Solutions (2018)

</td>  
<td>

Noskov A.

</td>  
<td>

Proceedings 7th

International

Conference on

Cartography and GIS

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_2018rastertiles_

_qualityinitial.pd_

_f_

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

Open Source Tools for

Coastal Dynamics

Monitoring (2018)

</td>  
<td>

Noskov A.

</td>  
<td>

Proc. SPIE 10773, Sixth

International

Conference on Remote

Sensing and

Geoinformation of the

Environment

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_2018osrccoastd_

_yn.pdf_

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

Backend and Frontend Strategies for Deployment of WebGIS Services (2018)

</td>  
<td>

Noskov A. and A. Zipf

</td>  
<td>

Proc. SPIE 10773, Sixth

International

Conference on Remote

Sensing and

Geoinformation of the

Environment

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_2018fbswebgis._

_pdf_

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

Smart City WebGIS

Applications: Proof of

Work Concept for Highlevel Quality-of-Service

Assurance (2018)

</td>  
<td>

Noskov, A.

</td>  
<td>

ISPRS Ann.

Photogramm. Remote

Sens. Spatial Inf. Sci.,

IV-4/W7

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_zipf2018pow.pd_

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

**Title (Year)**

</th>  
<th>

**Authors**

</th>  
<th>

**Journal/book/conferen ce**

</th>  
<th>

**Type**

</th>  
<th>

**Link to publication**

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

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

_f_

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

Definition of Contour Lines

Interpolation Optimal

Methodas for EGovernment Solutions

(2018)

</td>  
<td>

Noskov, A. and A. Zipf

</td>  
<td>

ISPRS Ann.

Photogramm. Remote

Sens. Spatial Inf. Sci.,

IV-4/W8

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_zipf2018interp._ _pdf_

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

Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-
History Dump (2019)

</td>  
<td>

Noskov, A. et al.

</td>  
<td>

Spatial Planning in the Big Data Revolution

</td>  
<td>

Book chapter

</td>  
<td>

_http://ar.nkov.com/i/Nosk_ _ovGrinbergerPa_ _papesiosRousell_
_TroiloZipf2019L_ _owLevelFHD.pd_

_f_

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

Open-Data Driven

Embeddable Quality

Management Services for

Map-Based Web

Applications (2019)

</td>  
<td>

Noskov, A. and A. Zipf

</td>  
<td>

Big Earth Data

</td>  
<td>

Journal Article

</td>  
<td>

_https://www.ge_ _og.uniheidelberg.de/_ _md/chemgeo/g_ _eog/gis/noskov_
_zipf2019embqu_

_ality.pdf_

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

From E-Government to We-Government: an analysis towards participatory public
services in the context of the H2020 WeGovNow

(2018)

</td>  
<td>

Tsampoulati

dis, I.,

Kompatsiaris

, I. and N.

Komninos

</td>  
<td>

Information Society and Smart Cities Conference University of Cambridge,
United

Kingdom

</td>  
<td>

Conference proceedings

</td>  
<td>

_https://zenodo._ _org/record/257_ _8929#.XJoSoKAi_

_FLw_

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

La Pubblica

Amministrazione responsabile : un caso di digital welfare (2018)

</td>  
<td>

Visentin, M.

and G. Antonini

</td>  
<td>

Rivista Italiana di Public Management

</td>  
<td>

Journal Article

</td>  
<td>

_https://zenodo._ _org/record/257_ _9141#.XJoSXaAi_

_FLx_

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

First Life, the

Neighborhood Social

Network: a Collaborative

Environment for Citizens

(2016)

</td>  
<td>

Antonini, A. et al.

</td>  
<td>

Proceedings of the 19th ACM Conference on

Computer Supported

Cooperative Work and

Social Computing

Companion

</td>  
<td>

Conference publication

</td>  
<td>

_https://iris.unit_

_o.it/handle/231_ _8/1646139#.XH_ _QHFaAiFhE_

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

WeGovNow: a map based platform to engage the local civic society (2018)

</td>  
<td>

Boella, G. et al.

</td>  
<td>

WWW '18 Companion

Proceedings of the The Web Conference 2018

</td>  
<td>

Conference publication

</td>  
<td>

_https://dl.acm._ _org/citation.cfm_ _?id=3191560_

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

WeGovNow: an integrated platform for social engagement in shaping future
cities (2018)

</td>  
<td>

Boella, G. et al.

</td>  
<td>

4th Italian Conference on ICT for Smart Cities And Communities 2018

</td>  
<td>

Conference publication

</td>  
<td>

_https://iris.unit_

_o.it/handle/231_ _8/1693782#.XH_

_P_aqAiFhE_

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

Back to public: Rethinking

</td>  
<td>

Lupi, L. et al.

</td>  
<td>

Proceedings of the

</td>  
<td>

Conference

</td>  
<td>

_https://iris.unit_

_o.it/handle/231_

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

**Title (Year)**

</td>  
<td>

**Authors**

</td>  
<td>

**Journal/book/conferen ce**

</td>  
<td>

**Type**

</td>  
<td>

**Link to publication**

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

the public dimension of institutional and private initiatives on an urban data

platform (2016)

</td>  
<td>

</td>  
<td>

2016 IEEE International

Smart Cities

Conference (ISC2)

</td>  
<td>

publication

</td>  
<td>

_8/1646137#.XH_

_QHiKAiFhE_

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

MiraMap: A We-

Government Tool for

Smart Peripheries in Smart

Cities (2016)

</td>  
<td>

De Filippi, F. at al.

</td>  
<td>

IEEE Access Journal

</td>  
<td>

Journal Article

</td>  
<td>

_https://ieeexplo_ _re.ieee.org/doc_ _ument/7444140_

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