#  Summary

This document provides the description of what data OpenUP project will
generate, how it will be stored and managed and how it will be preserved after
the end of the project. PPMI prepared this document as the main partner
leading task 1.4 with inputs from other consortium partners and with a review
from UoA. This Data Management Plan complies with H2020 requirements  1  and
is based on the DMP template  2  provided by the e-Infrastructures Austria
project. The plan will be updated whenever changes to the project are made due
to inclusion of new data sets, changes in consortium policies or other
external factors.

#  Explanatory Remarks

For creating a common ground of understanding, in the current deliverable we
use the following definition of dataset:

A dataset is any set of data (no matter how many files it materialises) that
is worth to be considered as a unit for data management activities  3

Any of the following can be considered as a possible dataset in the context of
a project:

  * Any dataset produced by aggregating data from data providers for analysing it; 

  

  * Any dataset produced by aggregating data from data providers for building an integrated dataset out of the aggregated data (e.g. this is the case of Knowledge Bases); 

  

  * The material of a training course; 

  

  * A dataset documenting and providing evidence for either a report or a publication produced in the context of project activities. 

  

In the case of OpenUP we have identified three main categories of datasets:

Core Datasets, i.e., datasets related to the main project activities (review-
assess-disseminate) and worth to be used by the project. These datasets pre-
exist OpenUP and are publicly available;

Produced Datasets, datasets resulting from the operation and evaluation of
OpenUP’s use cases and pilot applications. These may include but are not
limited to data collected through questionnaires, workshops, interviews, and
desktop research.

Project Related Data, i.e., datasets resulting from the operation of the
OpenUP project and produced by the OpenUP consortium. These datasets are
collections of standard material produced by a research project, e.g.
deliverables, dissemination material, training material, scientific
publications.

#  Data Collection  
  
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Data Collection

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Data collection activities will be carried out in WP3, WP4, WP5, WP6 and WP7.
Main data collection methods include survey, interviews, workshops, focus
groups, crowdsourcing, and web mining. Main data that the consortium will
generate include opinions, attitudes and practices of researchers regarding
open peer review, alternative dissemination and altmetrics.

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The raw data collected from surveys will be stored in a suitable format (e.g.
Excel files, ODS or CSV files).

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The recorded data from focus groups, workshops and interviews will be stored
as recordings in a suitable format (MP3, OGG or WMA format) on the internal
servers of the task leading organisations. If focus groups, workshops and
interviews are not recorded, the written summaries will be saved in a suitable
format (Word documents, text files). The data from crowd-sourcing will be
stored in Google Spreadsheets that anyone with the link can access.

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Files will be converted to open file formats where possible for long term
storage and in these cases the researchers will anonymise the data.

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3  Renear, A.H., Sacchi, S. and Wickett, K.M. (2010) Definitions of dataset in
the scientific and technical literature.

Proceedings of the American Society for Information Science and Technology,
47(1): 1–4. DOI:

_10.1002/meet.14504701240_

#  Data storage, selection and preservation and data sharing  
  
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Data Storage

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The raw data collected from the survey will be stored in a suitable format
(e.g. Excel files, ODS or CSV files). The documents will be saved on the
internal institutional server of the task leader (PPMI). The server is
protected by passwords known only to the researchers working on OpenUP
project. Unauthorised users will not be able to access the data. The documents
available on the server are backed up regularly. Once processed and
anonymised, the data will be published on an online repository (eg. Zenodo)
and will be available for the use by third parties.

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The recorded data from focus groups, workshops and interviews will be stored
as recordings in a suitable format (MP3, OGG or WMA format) on the internal
servers of the task leading organisations. If focus groups, workshops and
interviews are not recorded, the written summaries will be saved in a suitable
format (Word documents, text files) and will be also stored on the internal
servers of the responsible institution. The data will be backed up regularly.
The servers are password protected and only researchers working on the project
will be able to access the files. The written summaries will be anonymised and
will also be made available on the online repository for third parties’ use.

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The data from crowd-sourcing will be stored in Google Spreadsheets that anyone
with the link can access. Participants can enter data in the spreadsheet
either anonymously or by identifying themselves.

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All the collected data, apart from the crowd-sourced data, will be anonymised.
The information provided will be analysed and presented in project reports
grouped together and will not be used individually.

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Data storage

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The Raw data will be stored on the institutional servers of the organisations
that have generated them. The data will be stored for two years after the end
of the project. After that, the data will be destroyed.

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The anonymised data will be stored in an online repository (e.g. Zenodo).

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Data Sharing

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The raw data will only be accessed by researchers that collected the data. The
anonymised summaries of interviews and workshops or survey results will be
made accessible to other partners as well as third parties.

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#  Documentation and Metadata

The following table outlines an example structure of the metadata that project
partners will include to describe their data.  
  
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Project and GA number

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OpenUP 710722

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Data type

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Text document/ numerical data/ survey data

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Description

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Description of the variables and description of the data included

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Data state

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Processed

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Data source

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Interview/ workshop/ focus group/ data mining/ survey / crowdsourced data

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Media type

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The format the data is stored in

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Licence or use

constraints

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Licence (if any)

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Size

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Size of the file

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#  Ethics and Legal Compliance

The OpenUP project will mostly collect data on opinions, attitudes and
practices related to open peer review, innovative dissemination and novel
impact assessments methods used by the researchers. The consortium will also
collect some personal data (such as country, gender, career stage or a
researcher). Contact emails and names of researchers will be used when
inviting them to participate in the survey, interviews or workshops. Once the
data is collected, the researchers will anonymise it and present it in
aggregated manner. The procedures for data handling of OpenUP are described in
D8.1 data handling procedures document available  _here_ .  Also, participants
of interviews, workshops and survey will be informed about the OpenUP project
and the research activities through informed consent procedures that are
described in  _D8.2._

#  Responsibilities and Resources

PPMI is the lead for developing DMP and implementing it together with
participation of UoA. PPMI is also responsible to ensure that the plan is
reviewed and revised during the project duration. The DMP will be updated
whenever important changes to the project occur due to inclusion of new
datasets, changes in consortium policies or external factors. All involved
partners are responsible for the compliance with the DMP and the procedures
for data collection, handling and preservation.

The contact person for communication:

Viltė Banelytė

_Vilte@ppmi.lt_

+37062336168

No additional resources than those already outlined in the budget of OpenUP
will be needed for data management and archiving.