#  1\. Introduction

This deliverable concerns the **Data management plan** (DMP) for the EU-H2020-
PRISMA project.

PRISMA stands for: Piloting RRI in Industry: a roadmap for tranSforMAtive
technologies).

The **main objectives** of the PRISMA- project

  * Integration of Responsible Research and Innovation (RRI) in the CSR (corporate social responsibility) policies of 8 companies in the field of transformative technologies 

  

  * Providing evidence on how the RRI approach and attention for the gender dimension can improve the innovation process and its outcomes 

  

  * The development and dissemination of a roadmap that helps industries to implement RRI in their innovation processes as part of their CSR policy in order to deal with uncertain and sometimes partly unknown risks and public and ethical concerns of transformative technologies. 

  

The main data we will collect as part of this project are: case studies at
companies, benchmarks (like CSR-policies), results of stakeholder meetings,
interviews and surveys.

This DMP describes:

  * Which data will be collected in the different work package (par. 2) 

  

  * Which repository we will use (par. 3) 

  

  * How the data will be documented/metadata: par 4 (with more details in Annex 1 

  

  * How the data will be shared during and after the project and which data will be excluded from open access because of privacy reasons and commercial interest (par. 5 and Annex 2) 

  

  * Governance of the DMP (par 6.) 

  

We consider the data management plan to be a living document that – if need
be- will be updated over the course of the project. The data management plan
has interdependencies with the informed consent forms which we use for our
research activities.

This DMP was written in close consultation with the  _4TU.Centre for Research
Data_ (associated with the TU Delft) which mission is‘ to ensure the
accessibility of technical scientific research during and after completion of
research to give a quality boost to contemporary and future research.

This DMP is a living document and will be reviewed periodically.

#  2\. Data collection

The main data collected within this project are:

  * Literature studies 

  

  * Data on the 8 companies participating in the pilot 

  

  * Around 50 (indicative number) interviews (transcript, videos) 

  

  * Results of surveys among stakeholders - Results from workshops. 

  

The following data provides an overview of the data collected for each work
package:  
  
<table>  
<tr>  
<th>

**WP**

</th>  
<th>

Work Package Title

</th>  
<th>

**Lead**

</th>  
<th>

**Research Data and reports Collected**

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

1

</td>  
<td>

Design of RRI- pilots with industry

</td>  
<td>

RIVM

</td>  
<td>

  * From Literature: An inventory of the specific challenges that are posed by transformative technologies for RRI and strategies and tools to deal with this on the basis of the existing 

  

literature

  * From literature **:** Overview most appropriate RRI tools (literature **)**

  

  * Pilot company specific data (company policies, gender issues, internal procedures, planning, etc.) and pilot-company needs, wishes, possibilities and constraints (interviews, bestpractices). 

  

  * Interviews with selected companies: 

  

identification of CSR policy of pilot companies and of possibilities to
integrate RRI in that CSR policy

  * From literature: description of the technology domain as a contextual basis for the pilot studies. 

  

  * Case descriptions of the innovations developed in the pilot projects. 

  

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

2

</td>  
<td>

Implementation of pilots

</td>  
<td>

UWAR

</td>  
<td>

  * Report on kick-off workshops (synthesis) 

  

  * Report: Analysis of different view between technology and business ethicist 

  

  * Final report on pilots 

  

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

3

</td>  
<td>

Evaluation of pilots

</td>  
<td>

TU

Delft

</td>  
<td>

  * Report: Assessment of added value of RRI in industry based on pilots and additional projects 

  

  * Report Comparative analysis of the eight 

  

pilots

  * Feedback received from pilots 

  

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

4

</td>  
<td>

Stakeholder dialogues

</td>  
<td>

KIT

</td>  
<td>

Report on development of a dialogue and stakeholder mapping strategy. Report
on Mapping of stakeholders

Report on stakeholder dialogue workshops

Report on Dialogue Integration/feedback

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

5

</td>  
<td>

Roadmap

</td>  
<td>

AIRI

</td>  
<td>

Report: analysis of economic impact of RRI adoption

Report wrap-up of all the results and outputs of the WP2, WP3, WP4 and

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

6

</td>  
<td>

Dissemination

</td>  
<td>

TU

Delft

</td>  
<td>

Reports on the 3 open stakeholders’ workshops which aim at clear
recommendations for the RRICSR roadmap.

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

7

</td>  
<td>

Management

</td>  
<td>

TU

Delft

</td>  
<td>

n.a.

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

In summary, the data collected will be mainly qualitative and consists of
records of interviews and workshops as well as reports on findings.

Overview WP’s PRISMA project

#  3\. Data Storage and Back-up during the project

##  3.1 . Repository selected for storage during the project

For data storage _during the project_ we will use the following repository:
_DataverseNL_

DataverseNL is provided by  _4TU Centre for Research Data_ to researchers and
lecturers of the four technical universities in the Netherlands to store and
share the data that they create or compile during their research. DataverseNL
accepts data in all disciplines and formats.

Screenshot  _DataverseNL_

In section 4.2 we will provide more details on the 4TU Centre for Research
Data and the repository

##  3.2 A few words about the repository Dataverse.nl

  * Dataverse is an open source web application to share, preserve, cite, explore, and analyze research data. It facilitates making data available to others, and allows you to replicate others' work more easily. Researchers, data authors, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility. 

  

  * The Dataverse software is being developed at Harvard's  _Institute for Quantitative_ _Social Science (IQSS)_ ,  along with many collaborators and contributors worldwide. One of these contributors is the Dutch national institute  _DANS_ (Data Archiving and Networked Services). 

  

  * The mission of DANS is to promotes **sustained access** to digital research data files and to encourages researchers to **archive** and **reuse** data. 

  

  * The TU Delft and all its partners- can make use of this national repository without any restrictions. 

  

  * For data and other material in DataverseNL. A back-up is made each night and stored at 2 locations in the Netherlands. A back–up is kept for 3 months (retention time). 

  

  * This repository was also selected because: 

    * it allows to easily define and create different roles and reading rights (admin, 

  

  

curator, contributor, read only).

  * it can be used by all the researchers (in- and outside the TU Delft). 

  

  * because it is tailored for research in the alpha and gamma domains. 

  

**Below a Screenshot of _https://datave_ ** _ r **s** **e.nl/dvn/** _

#  4\. Data Archive (long term storage)

##  4.1 Repository

When the project has ended and data are ready to be archived and shared, they
will be transferred to a repository with a commitment to long-term
preservation. For this purpose we will use the ‘4TU.ResearchData’ data archive
which is a certified data repository for technical-scientific research data.
Each dataset deposited at ‘4TU.ResearchData’ is assigned a Digital Object
Identifier (DOI) which allows easy citation and discoverability.

##  4.2 A few words about ‘ 4TUResearchData’

The TU Delft is one of the founding members of the ‘ 4TU.ResearchData’ (also
known as the 4TU centre for Research Data). It’s mission is to ensure the
accessibility of technical scientific research during and after completion of
research to give a quality boost to contemporary and future research.

The organization offers the knowledge, experience and the tools to archive
research data in a standardized, secure and well-documented manner. It
provides the research community with:

  * A long-term archive for storing scientific research data 

  

  * Permanent access to, and tools for reuse of research data 

  

  * Advice and support on data management 

  

4TU.ResearchData currently hosts thousands of datasets. To see examples please
visit:  _http://data.4tu.nl_ .

#  5\. Data Documentation (metadata)

It goes without saying that generating metadata is highly important during
data collection in order to find and re-use the appropriate data.

When using DataverseNL for data storage and sharing during research it’s
required to add the cataloguing information (metadata) when submitting a
dataset. The metadata fields are designed for compliance with the  _Data
Documentation Initiative_ (DDI), an internationally recognized standard for
describing data.

For adding Metadata to the datasets we have developed a format which you can
find _in_ _Annex 1_ (NB: slightly modified from 4TU Research Data Centre
metadata form).

As far as the _process_ is concerned, the following can be added:

  * The responsible researcher of each case will take care of adding the meta-level information to the database by using the 'add new data' form as attached See par 4’. 

  

  * The responsible researcher uploads the respective original research documents to the selected repository. If this is not possible, (for instance because the research data is not collected during the PRISMA/ project or is owned by someone who is not part of the project) then at least the metadata has to be provided with information where the original, full document is located. 

  

  * The naming practices of files have to be distinct in order to achieve a clear structure in the database. 

  

Each file will begin with a short name given to the case under consideration.

After this comes the content related part of the file name such as “CEO
interview transcript” or “short case description”, and the version information
referring to the day, month and year, of the last alteration of the file. Then
the affiliation, version (dr =draft, fv = final version) and reviewer initials
if needed.  
  
<table>  
<tr>  
<th>

So, as an example:
PRISMA_WP3_"case"_”content”_”date”_”affiliation”_dr#_”reviewer

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

initials”.filetype

</td>  
<td>

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

  * So both draft and final versions can be stored in the database, but you have to include dr# or fv to the name. 

  

  * The responsible researcher is responsible that the access rights to each document are correct. 

  

  * The partners can search the data using the search tools provided for the repository The search result will show the metadata and provide and 'upload' link to the original research documents. 

  

  * Non-open data Data will be accessible to project participants only through username/password. 

  

More about Data Access and rights in the next paragraph.

**6\. Data & Access rights **

_General rules_

  * In general, data ownership is jointly shared among consortium partners. Commercial exploitation of data is not foreseen. 

  

  * Data gathered in the surveys and workshops will be made openly available via after the project has finished and scientific papers have been published and once it has been anonymized in such a way that it cannot be tracked back to individual respondents, directly nor indirectly.  1 

  

  * During the course of the project, these data will be stored and made available in and via Dataverse.nl (see par. 4), which complies fully with H2020 requirements. 

  

  * Data that we do not produce in the project (e.g. existing cases, existing survey data, informed consent forms, existing data from statistical offices) will not be made openly available. 

  

  * Research Data that is not privacy sensitive will be available open access through the data center mentioned above, after the project has finished and scientific papers have been published. 

  

  * We will work with Informed Consent (IC) forms for surveys, interviews, videos and workshops. These IC-forms will not form part of the dataset. However, we will publish the templates we used. Informed consent forms will be excluded from the open datasets. The IC-forms y can only be assessed by the researcher and the WP-leader. In line with the above, we will make interview summary reports available, but not the interview recording.| 

  

  * Data gathered in the **case studies** will also only be made openly available as long as it does not harm the competitiveness of the business being studied. See also Annex 2 for 

  

procedures.

  * All final publications, presentations and selected videos will -in principle- be published under a CC. 4.0 licence. 

  

_Access during the project_

  * WP-members can access and review all draft products which form part of their WP. Also the PI and the WP-leaders have access (but reading only) considering the strong link between the WP’s. 

  

  * Only the researcher is allowed to delete his or her own information/products. 

  

  * IC-forms and transcripts of interviews can only be accessed by the researcher involved and the WP-leader. If a dispute may arise, the PI will get access to these materials. 

  

#  7\. Governance

To safeguard compliance with all aforementioned data management decisions, the
following governance measures are applied:

  * WP leaders are responsible for adhering to the above specifications for their respective work package. For the overall project, TUD will be responsible for complying with the data management plan. All consortium partners are responsible for making sure personnel working on the project have read the data management plan and internalized the principles. Data management will be on the agenda in all executive board meetings as of September 2016. The 4TU Research data centre will give advice. 

  

  * The data management plan is considered a living document. New versions of the DMP should be created whenever important changes to the project occur due to inclusion of new data sets, changes in consortium policies or external factors ⮚ Updates to the data management will be communicated by the TU Deft 

  

To evaluate the efficacy of the data management plan, we will conduct an
evaluation in M18. The evaluation will at least include:

  * Is the metamodeling still consistent with what is being done in WP 1, 2, 3 4 and WP5? Is updating the meta-model required? 

  

  * Do the survey data include meaningful metadata (i.e. labels) that are understandable for outsiders? 

  

  * Are all personal data anonymized? 

  

  * Do the data gathered not harm privacy or the commercial interests of the company case studies 

  

  * Do informed consent forms align with the DMP (anonymized storage of data)