<table>  
<tr>  
<th>

</th>  
<th>

Immediate contributions of PRINTEGER will include raised attention for
realistic and effective integrity measures through dissemination, including a
large conference, and immediate trial and use of much improved educational
resources for teaching research ethics to future and young scientists.

**Website:** Printeger.eu

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

**The main data activities of**

**PRINTEGER**

</td>  
<td>

Besides the normal data activities of a EU funded research project (life
cycle) the DMP of PRINTEGER will focus on four activities:

  1. Web-based questionnaire (Task IV2); 

  

  2. Focus groups (Task IV3); 

  

  3. case studies (Task III3); 

  

  4. interviews. 

  

  

**_Web-based questionnaire_ ** .

Participants (approximately 2000) will be invited to participate on a
voluntary basis. An information sheet will be produced containing information
concerning the objectives of PRINTEGER and the way data will be managed.
Research data will be anonymous and no data will be collected that would make
participants identifiable.

Primary data will only be shared beyond the researchers immediately involved
in this specific work package after complete anonymity has been verified. The
objective is to analyse factors that promote or hamper integrity in research.
We will not collect or publish accusations of misconduct concerning
identifiable individual researchers or institutes. The objective of the
project and the data-management strategy will be carefully explained to
potential participants.

**_Focus groups_ . **

Participants (120) will be invited to participate on a voluntary basis. An
information sheet will be produced containing information concerning the
objectives of PRINTEGER and the way data will be managed.

Researchers commit to select a reasonable representation of gender, age,
position (student, professor, manager, etc.) and other relevant social
categories in the focus groups. The objective of the project and the
datamanagement strategy will be carefully explained.

We will not collect or publish accusations of misconduct concerning

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

</td>  
<td>

identifiable individual researchers or institutes. We will take care not to
give rise to stigmatisation (information on ‘ethnicity’ or religion for
instance, will not be part of our data).

Reports of sessions will be anonymous and draft versions will be distributed
among participants for comments and corrections. We will articulate conditions
of privacy and confidentiality of the data also in the information sheet.

**_Case studies_ : **

The consortium will use secondary analysis, that is, the consortium will
analyse case materials already available in the public domain. This also
applies to Institutional responses to scientific misconduct studied by
PRINTEGER: this again refers to materials available in the public domain. In
some cases, interviews will be used to shed light on the cases. For this
method, please see the considerations immediately below.

**_Interviews_ ** :

Experts will be invited to participate on a voluntary basis. Before the
interview, The objective of the project and the strategy for data-management
and data-analysis will be carefully explained with the help of the PRINTEGER
information sheet explaining objectives and data management strategy.

We will articulate feedback of the results to the participants of the
interviews. Draft reports of the interviews will be presented to participants
for corrections. Reports will be anonymised, unless explicit consent for
quoting identifiable participant views has been acquired.

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

#  Data management roles  
  
<table>  
<tr>  
<th>

**Who is involved in writing the DMP?**

</th>  
<th>

The Project Management Team (RU) will prepare a Data Management Plan in which
the participants determine and explain which of the generated (research) data
will be made open or reasons for not giving access.

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

**Data Manager PRINTEGER / role**

</td>  
<td>

Willem Halffman will act as Data Manager PRINTEGER. He shall be responsible
for executing the DMP PRINTEGER. Every consortium meeting the Data Manager
will provide an update and discuss (strategic) issues with the partners / EAB
members like approval for access. He shall act as focal point for matters
regarding requests from partners outside the consortium, situations like loss
of data etc.

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

**Who is creating the data?**

</td>  
<td>

Project Partners

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

**Who is processing and analysing the data?**

</td>  
<td>

Project Partners

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

**Who is preserving and giving access to the data?**

</td>  
<td>

**During the project** : project partners are responsible for preserving data
and giving access to data in line with the DMP PRINTEGER.

All PRINTEGER deliverables will be made freely available to a wide audience
through the website Printeger.eu and active dissemination.

**After project completion** : Vital resources will be made available also
beyond the duration of the project, e.g.: - _Educational tools_ : will
continue to be curated by RU, as they will function in the daily educational
activities of RU. In the unlikely event that RU web servers prove unwieldy or
technical support falls short, then another host with active interest in
teaching will be found.

\- _Misconduct incidence data_ , the code and guideline inventory, researcher
leader tools, and similar output that will continue to be of active use beyond
PRINTEGER will be hosted by a large and stable research organization that has
an active interest in the curation of such resources. For such purposes, the
project manager will seek cooperation with an academy of science or
professional organisation, such as ALLEA.

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

**Who owns the data?**

</td>  
<td>

Data are owned by the project partner that generates them

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

**Who may want to reuse the data?**

</td>  
<td>

Researchers, research funding organisations, National and local policymakers
[..]

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

**Supervision**

</td>  
<td>

Expert Advisory Board (EAB) of PRINTEGER. Their supervision is of particular
importance for misconduct incidence data, but arrangements will be made to
provide access to data, under restrictions of privacy.

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

**Are there any other roles concerning research data management of importance
for your research?**

</td>  
<td>

All Partners will work closely with their local Data

Management Officers and Data Security Officers in order to comply with the
local and national rules and regulations. Information which is of importance
for this DMP shall be communicated directly to the Data Manager PRINTEGER.

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

#  Data standards and security

##  Data Standards

All data in PRINTEGER will be collected using the principles and best
practices of qualitative and quantitative data collection. For example
interviews will be undertaken with informed consent of the interviewees and
participants (more on this in Section 4), the goals will be communicated to
them clearly, and recorded answers will be checked with the
interviewees/participants.

Every dataset will contain instructions (readme.txt) and if needed quality
testing information (eg. methodology). Files and folders will be versioned and
structured using a name convention consisting of Work Package name, task name
(Figure 1), and file name. The file naming convention is: short name of file
contents, date and version number (Figure 2).

**Figure 1)** Example of PRINTEGER **Figure 2)** Example of PRINTEGER file
data structuring convention naming convention

Analysis of the data will be performed using standard software (e.g. MS
Office, Windows Media Player, SPSS, NVivo) provided by host institutions or
freely available open source software tools. The short- and long-term storage
of the data belong to the project partner that generated it.

##  Security

Partners will take all necessary measures in order to prevent loss of data.
This will include the protection of primary data by keeping data out of the
cloud and other sharing services that go beyond the local research
organization. If needed, Partners will get advice and approval from their Data
Security Manager about using specific programmes and services.

Access to unprocessed primary data will be restricted to researchers involved,
through secure data storage. This point will be addressed in the appropriate
deliverable.

Loss of data is safeguarded against by:

  * storing the data on secure servers supervised by project partners’ host institutions; 

  

  * regular backing up of the data on the abovementioned servers; 

  

  * encrypting all of the data by the abovementioned institutions as soon as it is stored on their servers. 

  

Sharing of the data and levels of access are explained in Section 5\.

#  Privacy

We will adhere to local and national ethical rules and guidelines as well as
with national and EU legislation. Overall, our project does not involve the
use of identifiable data relating to persons. To the extent that identifiable
data (quotes etc.) will be used, explicit consent will be acquired in
accordance with research ethics guidelines and best practices.

Participation of persons (as respondents in interviews or participants in
interviews, survey, focus groups) will be _entirely voluntary_ . We will
obtain (and clearly document) their informed consent in advance. For this
purpose, we will prepare an informed consent form and a detailed information
sheets which:

  * are in a language and in terms fully understandable to them; 

  

  * describe the aims, methods and implications of the research, the nature of the participation and any benefits, risks or discomfort that might be involved; 

  

  * explicitly state that participation is voluntary and that anyone has the right to refuse to participate — without any consequences; 

  

  * indicate how (personal) data will be collected, protected during the project 

  

  * describe how anonymised data will be stored for transparency reasons, but not for future reuse; 

  

The consortium ensures that the potential participant has fully understood the
information and does not feel pressured or forced to give consent. If the
consent cannot be given in writing, for example because of illiteracy, the
non-written consent will be formally documented and independently witnessed.

Also our participants are _not_ used as ‘research subjects’ in the sense of
traditional social science research, but as professionals, academics and
research managers, that is: as sources of insight and information, and as
_active_ participants in the project, in accordance with the concept of
responsible research and innovation (RRI). _In other_ _words, they are not
mere sources of project data, but contributors to a co-constructive_ _and
interactive process_ .

We will point out that, rather than ‘benefits, risks or discomfort’, the
participation will allow participants to contribute to a co-creative and
interactive process designed to strengthen integrity in research. We will
clearly explain nonetheless what participation entails, for instance in terms
of amount of time. It will be explicitly statement that participants have the
right not to participate in the project, although we expect this to be
obvious, and that they are entitled to withdraw their participation without
any consequences at all stages.

Informed consent procedures will be installed in accordance with policy and
regulations of participating countries and universities.

##  Unexpected findings

During the first consortium meeting, we not only agreed on informed consent
procedures and data management plan in outline, but also discussed the issue
of how to act in the case of unexpected findings.

  * The consortium members are aware of the fact that we are collecting and processing data on sensitive issues (misconduct, integrity) which can have an impact in careers of individuals and on the reputation of institutions, or even on research as such. Privacy and anonymity must be respected. 

  

  * Data and findings must be processed in such a way that stigmatisation of groups or institutes is prevented. 

  

  * we are interested in factors that promote or deter integrity, not in allegations concerning traceable / identifiable individuals or institutions; it is not the task of the consortium to detect or report individual or institutional cases of scientific misconduct. Should we be informed about cases of misconduct, for instance in the context of interviews or focus groups, we may encourage participants to seek advice from local integrity offices or local integrity board, but it is not our task to undertake such actions ourselves. 

  

  * Nonetheless, it may be the case that, in the course of our project, consortium members will be provided with evidence concerning extreme cases of fraud and misconduct in such a way that serious conflicts of conscience may arise and the principle of confidentiality comes under pressure. For instance: cases of largescale financial fraud or sexual exploitation. We have decided that, should such a situation arise, we will call a consortium meeting and decide on the basis of unanimity how to deal with the data in this case. 

  

#  Overview of research data / draft

##  Data used during research

These data are primarily for internal use. It is shared within the project via
a Dropbox folder or a specific sharing program (short-term storage) which
follows data privacy and security standards described in Sections 3 and 4.

Long-term storage of these data will be provided by the servers of the host
institution of the partner which generated the data.  
  
<table>  
<tr>  
<th>

**Task**

</th>  
<th>

**Description**

</th>  
<th>

**Stage**

</th>  
<th>

**Source**

</th>  
<th>

**Access level**

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

</td>  
<td>

Database of stakeholders with their personal data

</td>  
<td>

Raw

</td>  
<td>

Own contacts

</td>  
<td>

Restricted to project partners

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

II.1

</td>  
<td>

Inventory of key documents

</td>  
<td>

Analysed

</td>  
<td>

Own research

</td>  
<td>

Public

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

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

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

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

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

IV.3

</td>  
<td>

Focus groups

</td>  
<td>

Raw

</td>  
<td>

Own research

</td>  
<td>

Restricted to project partners

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

</td>  
<td>

Focus group report

</td>  
<td>

Analysed

</td>  
<td>

Own research

</td>  
<td>

Public

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

IV.2

</td>  
<td>

Questback Survey

</td>  
<td>

Raw

</td>  
<td>

Own research

</td>  
<td>

Restricted to immediately involved researchers

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

</td>  
<td>

Paper/report presenting results from the survey

</td>  
<td>

Analysed

</td>  
<td>

Own research

</td>  
<td>

Public

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

##  Data shared after research project completion

The columns Stage, Source, and Access are omitted for the data below since
they are the same for all of them. Thus, the Stage for all of these data sets
is “Analysed”, the Source is “Own research”, and the Access level is “Public”.
Long-term storage for these data will be provided via the project website (
_http://printeger.eu_ )  and the knowledge platform (to be announced).  
  
<table>  
<tr>  
<th>

**Task**

</th>  
<th>

**Description**

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

II.1

</td>  
<td>

Inventory of key documents

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

</td>  
<td>

interviews’ results  1  
</td> </tr>  
<tr>  
<td>

IV.2

</td>  
<td>

Survey Scheme

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

</td>  
<td>

Paper/reports presenting results from the survey

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

IV.3

</td>  
<td>

Focus group report

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

</td>  
<td>

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

##  Data size  
  
<table>  
<tr>  
<th>

**Task**

</th>  
<th>

**Description**

</th>  
<th>

**Data size**

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

</td>  
<td>

Database of stakeholders

</td>  
<td>

< 1 MB

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

</td>  
<td>

</td>  
<td>

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

IV.2

</td>  
<td>

Survey report

</td>  
<td>

5 MB

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

IV.3

</td>  
<td>

Focus group report

</td>  
<td>

< 1 MB

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

</td>  
<td>

</td>  
<td>

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

</td>  
<td>

</td>  
<td>

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

</td>  
<td>

</td>  
<td>

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

</td>  
<td>

</td>  
<td>

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

#  Appendix I Type of research data

_Type of research data_

Try to identify possible **types of research data** as early in your research
as possible. You may at least distinguish between the following three data
stages:

  * **Raw data** : this is the original data that you collected but did not process or analyse yet. For instance: audio files, archives, observations, field notes, data from experiments. When you reuse existing data – data you haven’t collected yourself – these data may be considered raw data. 

  

  * **Processed data** : this is the data that you digitised, translated, transcribed, cleaned, validated, checked and / or anonymised. 

  

  * **Analysed data** : these are the models, graphs, tables, texts etc. you created based on the raw and processed data, aimed at discovering useful information, suggesting conclusions and supporting decision-making. 

  

Be aware that when you haven’t created the data yourself, this may influence
what you are allowed to do with the data ( _data ownership_ ).

_Examples of the diverse types of research data are_ :

  * Documents (text, MS Word), spread sheets 

  

  * Scanned laboratory notebooks, field notebooks and diaries 

  

  * Online questionnaires, transcripts and surveys 

  

  * Digital audio and video recordings 

  

  * Transcribed test responses 

  

  * Database contents 

  

  * Digital models, algorithms and scripts 

  

  * Contents of an application (input, output, log files for analysis software, simulation software and schemas) 

  

  * Documented methodologies and workflows 

  

  * Records of standard operating procedures and protocols 

  

#  Appendix II Dataflow  
  
<table>  
<tr>  
<th>

**Phase 1. Creating data**

  * design research 

  

  * plan data management (formats, storage, etc.) 

  

  * plan consent for sharing 

  

  * locate existing data 

  

  * collect data (experiment, observe, 

  

measure, simulate)

  * capture and create metadata 

  

</th>  
<th>

</th>  
<th>

**Phase 2. Processing data**

  * enter, digitise, transcribe, translate data 

  

  * check, validate, clean data 

  

  * anonymise data where necessary 

  

  * describe data 

  

  * manage and store data 

  

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

**Phase 3. Analysing data**

  * interpret data 

  

  * derive data 

  

  * produce research outputs 

  

  * author publications 

  

  * prepare data for preservation 

  

</td>  
<td>

</td>  
<td>

**Phase 4. Archiving data**

  * migrate data to the best format 

  

  * migrate data to a suitable medium or media 

  

  * back up and store data 

  

  * create metadata and documentation 

  

  * archive data 

  

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

**Phase 5. Giving access to data**

  * distribute data 

  

  * share data 

  

  * control access to data 

  

  * establish copyright 

  

  * promote data 

  

</td>  
<td>

</td>  
<td>

**Phase 6. Reusing data**

  * follow up on research 

  

  * carry out new research 

  

  * conduct research reviews 

  

  * scrutinise findings 

  

  * teach and learn 

  

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

_**Radboud University policy for storage and management of research data** _

_**(Executive Board decision dated 25-11-2013)** _

**Appendix III Informed consent form**

#  Appendix IV Agreements