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From Open Access to Open Data
collaborative work
in the university libraries of Catalonia
Mireia Alcalá & Lluís Anglada (CSUC)
supported by the Research Support Working Group of CSUC
1. Who we are
2. Work done with research data
3. Work in progress with research data
4. Conclusions
1.1 New merged consortium in 2014
• for Catalan universities
• with more services and projects
– the CBUC activities
• Union catalogue, ILL, ILS…
– the CESCA activities
• Network, supercomputing…
– CSUC new activities
• join purchases (electricity, printing, cleaning,
facilities, etc.)
• common data center
• portal for the research output (PRC)
1.2 Libraries evolution: from print to digital
from an object centred
organization and services
to a process centred
organization and services
1.3 Evolution of Catalan university libraries activities and
organization supporting research
• Traditional activities supporting research:
– Collection buildings
• Acquisitions, Journals collections, Special collections…
– The big change of the networked digital information
• The content is on your PC, tablet, mobile…
• New tools and rules are completely strange to the majority of researchers
– Identifiers, OA, mandates, altmetrics…
• Open Science as the new landscape
• Our evolution supporting research
– Since 2005 (approx.), Catalan university libraries made changes in their services and
organization to adapt to the new situation
• subject librarians, reference management tools, open access…
– In 2013, CBUC had also changed and created a new strategic line for supporting research
• repositories, Mendeley, portal for Catalan research, OA…
– but Internet is disruptive, and in 2017 (Feb) we decided to be more radical and create a
new (small) area devoted to 'Open Science’
• open metadata (portal for Catalan research), open access, open data…
1.4 The CSUC and research
Commission of
vice rector for research
Research support
working group
Commission of
Research Portal
1.4 Research Support Working Group
2.1 Work done with the research data
• In 2015 the working group decided to focus on RDM:
Training
Exploring needs
from researchers
Research data
management plan
Recommendations
on data repositories
Framework
agreement of data
policy
• Training
– At CSUC level, inviting experts from other countries
– At university level, organizing staff training courses
• Survey
– We sent a survey to the leaders of the H2020 projects in the Catalan universities (included or not
in the Open Research Data Pilot)
– Aim: to know their needs RDMResults: nothing clear (due to our inexperience in RDM but also -
probably- because the researchers don't know exactly what they have to do)
– Report is available at RECERCAT and the associated data at ZENODO (http://hdl.handle.net/2072/268186 &
https://doi.org/10.5281/zenodo.183129)
2.2 Training and exploring researchers needs
• Guide on what a DMP should include according to the guidelines of the H2020
framework programme, which includes the FAIR principles and is accompanied
by selected examples from several real DMPs
2.3 Data Management Plans
• This guide is available in text
format in English (hdl.handle.net/2072/266523)
and Catalan (hdl.handle.net/2072/266502)
• Also, in the online tool “Research
Data Management Plan”
(www.dmp.csuc.cat), an
adaptation of the DMPOnline tool
of the Digital Curation Centre
2.3 DMP – Collective template
2.4 DMP – Individual specifications
2.5 DMP – Individual specifications
• The document provides sources for consulting:
– disciplinary repositories (directories, publishers' recommendations, etc.)
– multidisciplinary repositories (a comparative table showing the type of data allowed,
the file size, the associated licences, the cost of depositing, etc.).
2.6 Recommendations to support researchers in selecting a repository
http://hdl.handle.net/2072/266502
• Framework agreement for open access to research data
supported by the vice rectors for Research of the Universities of
Catalonia (https://goo.gl/w6LcJk)
2.7 Research data policy
• Models: “Policy RECommendations
for Open Access to Research Data
in Europe (RECODE)” and “Model
Policy for Research Data
Management (RDM) at Research
Institutions/Institutes” (LEARN)
• Since the service officially started (October 2016) we have been collecting the actions
associated to the RDM in universities
• These actions were measured with provisional indicators after the first 3 months of
the service. They are currently collected periodically every 6 months
• The indicators used are:
– H2020 projects
– Staff involved in RDM
– Training and RDM activities
– RDM queries received
– Visits received on the RDM website
– Users registered in the DMP tool
– Real plans created in the DMP tool
• The big gap: a lot of actions, very few plans created!
2.8 Monitoring
3.1 Our vision: different needs
FEW
SOME
QUITE A FEW
LOTS
RECOM
MENDA
TIONS
INSTITUTIONAL REPOSITORY
WITH DATA
SPECIAL CASES
RESEARCH DATA MANAGEMENT
REPOSITORY(S)
RESEARCH DATA REPOSITORY(S)
MANAGEMENT
PRESERVATION
PUBLICATION
RESEARCHERS
s0
s1
s2
s3
s4
s5
NEEDS
3.2 Our vision: different steps
F1
F4
F3
F2
F5
RDMP
Recommendations
IR with data
Special cases
Research data repository(s)
Research data management repository(s)
Short
Short-Medium
Medium
Medium-Long
Long
Step 1 - Recommendations
• As the needs differ a lot between disciplines, and, for the
moment, we are not able to offer a university or Catalan
repository…
• we will continue improving and getting up to date the
recommendations
• This, added to RDM Plans, is a small but real service
Step 2 - Adapt the existing repositories
to hold data
• Some Catalan universities have adapted their institutional repositories to permit
research data deposit in order to respond:
– requirements of the H2020 Open Research Data Pilot
– editorial policies that request authors a permanent link to the data
• Modifications:
– Use of HANDLE
– The same tasks in terms of preservation and storage than the rest of the files
– All universities have mapped OAI outputs to be interoperable with OpenAIRE
– Differences to inform the typology of data in “dc.type” metadata
– Data are grouped by type in collections
– Volumetric issues were not considered
• This in not the solution, but
– It’s easy and cheap to do it
– Allow us to archive some type of data (in very restricted conditions)
Step 3 – Pilot project
• Some researchers (not a lot) have immediate and sophisticated needs in
respect research data
– some ones have disciplinary solutions (genetics, astrophysics...), but others, not
– We don’t have an institutional or Catalan repository for them (neither we will
have it in the next two years)
– These researchers are very motivated and they know data better than us
• Characteristics of the 3 years pilot project (2018-20)
– Central payment (and only for 3 years) for a commercial solution + to hire a data
curator
– A group of 10-15 research groups highly motivated with one member of the group
as RDM leader
– RDM leaders + data curator = learning group
– Functions of Learning Group:
• share experiences and knowledge
• annual accountability report
• help in determining functional requirements for the research data repository (step 4)
Step 4 - Research data repository
• A commercial solution (step 3) seems not to be a feasible solution
for all (step 5)
– for cost,
– for strategical reasons,
– for interconnecting the RDR with other elements of the system
• 2017-18 objective: to determine functional requirements of the
research data repository (RDR has to be a FAIR repository)
– Permanent identifiers
– Storage of high dimensions
– Storage of different formats
– Preservation of high performance
– Interoperability
– Management of special features
• Challenges of the research data repository
– Involve all the stakeholders in the university
• Vice rectors and researchers / Library, Research Office, ITC, etc.
– To be one element of the system (jointly with IR, CRIS, Portal…)
Step 5 - Research data management repository
• As we have a lot of work to do before we arrive here, and
• a lot of unknown things can happen in the meantime
• we are not working on it (for the moment), except watching new
developments
1. Who we are
2. Work done with research data
3. Work in progress with research data
4. Conclusions
4. Conclusions, or, What we have learned
• There is a very big gap
• Cooperation is not altruism
When we talk about research data, there is a very big gap
• When we talk about research data…
̶ a big gap between disciplines
̶ a big gap between diagnosis and action
̶ a big gap between what the bests are doing and what the
rest can do
̶ a big gap between senior and junior researchers
̶ a big gap between Vice rectors and other ranking-worried-
officers and researchers
̶ a big gap between trendy and reality
̶ a big gap between the view of IT people and librarians
approach, and archivist vision and...
̶ a big gap between..
• Two learnings
• Start the way today but start it modestly
• Don't stop but don't want to be the first,
• In the new paradigm (Open Science), probably, the big change is not on tools, but
it’s on processes
• and the key question is: where libraries have to be in the chain?
Cooperation is not altruism
• Maurice B. Line (“Co-operation: the triumph of hope over experience?” 1997):
– Cooperation (like second weddings) often represents "the triumph of hope
over experience”, and
– “cooperation should not be undertaken unless it is likely to produce better
results than would be achieved by other means”
• Cooperation is costly
– You need to align different needs and speeds between different institutions
– You have to invest a lot in communication
• Two learnings
– Sometimes cooperation is the unique opportunity to create a new service
– Cooperation makes easy to get results, results are better and more accepted
lluis.anglada@csuc.cat · @lluisanglada
http://www.csuc.cat/en
Thanks!
Any question?

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From Open Access to Open Data: collaborative work in the university libraries in Catalonia

  • 1. From Open Access to Open Data collaborative work in the university libraries of Catalonia Mireia Alcalá & Lluís Anglada (CSUC) supported by the Research Support Working Group of CSUC
  • 2. 1. Who we are 2. Work done with research data 3. Work in progress with research data 4. Conclusions
  • 3. 1.1 New merged consortium in 2014 • for Catalan universities • with more services and projects – the CBUC activities • Union catalogue, ILL, ILS… – the CESCA activities • Network, supercomputing… – CSUC new activities • join purchases (electricity, printing, cleaning, facilities, etc.) • common data center • portal for the research output (PRC)
  • 4. 1.2 Libraries evolution: from print to digital from an object centred organization and services to a process centred organization and services
  • 5. 1.3 Evolution of Catalan university libraries activities and organization supporting research • Traditional activities supporting research: – Collection buildings • Acquisitions, Journals collections, Special collections… – The big change of the networked digital information • The content is on your PC, tablet, mobile… • New tools and rules are completely strange to the majority of researchers – Identifiers, OA, mandates, altmetrics… • Open Science as the new landscape • Our evolution supporting research – Since 2005 (approx.), Catalan university libraries made changes in their services and organization to adapt to the new situation • subject librarians, reference management tools, open access… – In 2013, CBUC had also changed and created a new strategic line for supporting research • repositories, Mendeley, portal for Catalan research, OA… – but Internet is disruptive, and in 2017 (Feb) we decided to be more radical and create a new (small) area devoted to 'Open Science’ • open metadata (portal for Catalan research), open access, open data…
  • 6. 1.4 The CSUC and research Commission of vice rector for research Research support working group Commission of Research Portal
  • 7. 1.4 Research Support Working Group
  • 8. 2.1 Work done with the research data • In 2015 the working group decided to focus on RDM: Training Exploring needs from researchers Research data management plan Recommendations on data repositories Framework agreement of data policy
  • 9. • Training – At CSUC level, inviting experts from other countries – At university level, organizing staff training courses • Survey – We sent a survey to the leaders of the H2020 projects in the Catalan universities (included or not in the Open Research Data Pilot) – Aim: to know their needs RDMResults: nothing clear (due to our inexperience in RDM but also - probably- because the researchers don't know exactly what they have to do) – Report is available at RECERCAT and the associated data at ZENODO (http://hdl.handle.net/2072/268186 & https://doi.org/10.5281/zenodo.183129) 2.2 Training and exploring researchers needs
  • 10. • Guide on what a DMP should include according to the guidelines of the H2020 framework programme, which includes the FAIR principles and is accompanied by selected examples from several real DMPs 2.3 Data Management Plans • This guide is available in text format in English (hdl.handle.net/2072/266523) and Catalan (hdl.handle.net/2072/266502) • Also, in the online tool “Research Data Management Plan” (www.dmp.csuc.cat), an adaptation of the DMPOnline tool of the Digital Curation Centre
  • 11. 2.3 DMP – Collective template
  • 12. 2.4 DMP – Individual specifications
  • 13. 2.5 DMP – Individual specifications
  • 14. • The document provides sources for consulting: – disciplinary repositories (directories, publishers' recommendations, etc.) – multidisciplinary repositories (a comparative table showing the type of data allowed, the file size, the associated licences, the cost of depositing, etc.). 2.6 Recommendations to support researchers in selecting a repository http://hdl.handle.net/2072/266502
  • 15. • Framework agreement for open access to research data supported by the vice rectors for Research of the Universities of Catalonia (https://goo.gl/w6LcJk) 2.7 Research data policy • Models: “Policy RECommendations for Open Access to Research Data in Europe (RECODE)” and “Model Policy for Research Data Management (RDM) at Research Institutions/Institutes” (LEARN)
  • 16. • Since the service officially started (October 2016) we have been collecting the actions associated to the RDM in universities • These actions were measured with provisional indicators after the first 3 months of the service. They are currently collected periodically every 6 months • The indicators used are: – H2020 projects – Staff involved in RDM – Training and RDM activities – RDM queries received – Visits received on the RDM website – Users registered in the DMP tool – Real plans created in the DMP tool • The big gap: a lot of actions, very few plans created! 2.8 Monitoring
  • 17. 3.1 Our vision: different needs FEW SOME QUITE A FEW LOTS RECOM MENDA TIONS INSTITUTIONAL REPOSITORY WITH DATA SPECIAL CASES RESEARCH DATA MANAGEMENT REPOSITORY(S) RESEARCH DATA REPOSITORY(S) MANAGEMENT PRESERVATION PUBLICATION RESEARCHERS s0 s1 s2 s3 s4 s5 NEEDS
  • 18. 3.2 Our vision: different steps F1 F4 F3 F2 F5 RDMP Recommendations IR with data Special cases Research data repository(s) Research data management repository(s) Short Short-Medium Medium Medium-Long Long
  • 19. Step 1 - Recommendations • As the needs differ a lot between disciplines, and, for the moment, we are not able to offer a university or Catalan repository… • we will continue improving and getting up to date the recommendations • This, added to RDM Plans, is a small but real service
  • 20. Step 2 - Adapt the existing repositories to hold data • Some Catalan universities have adapted their institutional repositories to permit research data deposit in order to respond: – requirements of the H2020 Open Research Data Pilot – editorial policies that request authors a permanent link to the data • Modifications: – Use of HANDLE – The same tasks in terms of preservation and storage than the rest of the files – All universities have mapped OAI outputs to be interoperable with OpenAIRE – Differences to inform the typology of data in “dc.type” metadata – Data are grouped by type in collections – Volumetric issues were not considered • This in not the solution, but – It’s easy and cheap to do it – Allow us to archive some type of data (in very restricted conditions)
  • 21. Step 3 – Pilot project • Some researchers (not a lot) have immediate and sophisticated needs in respect research data – some ones have disciplinary solutions (genetics, astrophysics...), but others, not – We don’t have an institutional or Catalan repository for them (neither we will have it in the next two years) – These researchers are very motivated and they know data better than us • Characteristics of the 3 years pilot project (2018-20) – Central payment (and only for 3 years) for a commercial solution + to hire a data curator – A group of 10-15 research groups highly motivated with one member of the group as RDM leader – RDM leaders + data curator = learning group – Functions of Learning Group: • share experiences and knowledge • annual accountability report • help in determining functional requirements for the research data repository (step 4)
  • 22. Step 4 - Research data repository • A commercial solution (step 3) seems not to be a feasible solution for all (step 5) – for cost, – for strategical reasons, – for interconnecting the RDR with other elements of the system • 2017-18 objective: to determine functional requirements of the research data repository (RDR has to be a FAIR repository) – Permanent identifiers – Storage of high dimensions – Storage of different formats – Preservation of high performance – Interoperability – Management of special features • Challenges of the research data repository – Involve all the stakeholders in the university • Vice rectors and researchers / Library, Research Office, ITC, etc. – To be one element of the system (jointly with IR, CRIS, Portal…)
  • 23. Step 5 - Research data management repository • As we have a lot of work to do before we arrive here, and • a lot of unknown things can happen in the meantime • we are not working on it (for the moment), except watching new developments
  • 24. 1. Who we are 2. Work done with research data 3. Work in progress with research data 4. Conclusions
  • 25. 4. Conclusions, or, What we have learned • There is a very big gap • Cooperation is not altruism
  • 26. When we talk about research data, there is a very big gap • When we talk about research data… ̶ a big gap between disciplines ̶ a big gap between diagnosis and action ̶ a big gap between what the bests are doing and what the rest can do ̶ a big gap between senior and junior researchers ̶ a big gap between Vice rectors and other ranking-worried- officers and researchers ̶ a big gap between trendy and reality ̶ a big gap between the view of IT people and librarians approach, and archivist vision and... ̶ a big gap between.. • Two learnings • Start the way today but start it modestly • Don't stop but don't want to be the first, • In the new paradigm (Open Science), probably, the big change is not on tools, but it’s on processes • and the key question is: where libraries have to be in the chain?
  • 27. Cooperation is not altruism • Maurice B. Line (“Co-operation: the triumph of hope over experience?” 1997): – Cooperation (like second weddings) often represents "the triumph of hope over experience”, and – “cooperation should not be undertaken unless it is likely to produce better results than would be achieved by other means” • Cooperation is costly – You need to align different needs and speeds between different institutions – You have to invest a lot in communication • Two learnings – Sometimes cooperation is the unique opportunity to create a new service – Cooperation makes easy to get results, results are better and more accepted

Editor's Notes

  • #28: Maurice B. Line “Co-operation: the triumph of hope over experience?”,. Maurice B. Line, (1997) "Co‐operation: the triumph of hope over experience?", Interlending & Document Supply, Vol. 25 Issue: 2, pp.64-72, https://doi.org/10.1108/02641619710167784