Europa: requisitos y servicios en torno a los datos de investigación por Remedios Melero

1. Europa: requisitos y servicios en
torno a los datos de investigación
Remedios Melero (IATA –CSIC)
rmelero@iata.csic.es
1

2. • Los datos de investigación parte
integrante de la open science
• Europa vs Open Science
• ¿Qué requiere Europa?
• ¿Qué ofrece Europa?
• Algunos retos
A tratar…..
2

3. http://ec.europa.eu/research/consultations/science-2.0/background.pdf
3
‘Science 2.0’ ( then
coined open
science) as a
holistic approach,
therefore, is much
more than only one
of its features (such
as Open Access)
and represents a
paradigm shift in
the modus
operandi
of research and
science impacting
the entire scientific
process”
Opening up of the research process

4. Infraestructura
/Tecnología
Ciencia accesible a los
ciudadanos
Nuevas métricasAcceso universal al
conocimiento
Generación del conocimiento
es más eficiente en
colaboración
Open Science: One Term, Five Schools of Thought. Benedikt Fecher & Sascha Friesike
http://book.openingscience.org/basics_background/open_science_one_term_five_schools_of_thought.html

5. ¿Para qué?
¿Por qué?
Career advancement
• Find new projects and collaborators
• Institutional support of open research practices
McKiernan, E. C., Bourne, P. E., Brown, C. T., Buck, S., Kenall, A., Lin, J., … Yarkoni, T.
(2016). How open science helps researchers succeed. eLife, 5, e16800.
http://doi.org/10.7554/eLife.16800
Publishing
• Open publications get more citations
• Open publications get more media coverage
• Prestige and journal impact factor
• Rigorous and transparent peer review
• Publish where you want and archive openly
• Retain author rights and control reuse with open licenses
• Publish for low-cost or no-cost
Funding
• Awards and special funding
• Funder mandates on article and data sharing
• Resource management and sharing
• Awards and special funding
• Funder mandates on article and data sharing
Resource management and sharing
• Documentation and reproducibility benefits
• Gain more citations and visibility by sharing data
Mas citas, mayor
diseminación
Transparencia
Cumplimiento con
políticas de
entidades
financiadoras
Compartir datos
contribuye a la
reproducibilidad
Contribuye a
generar nuevas
colaboraciones en
proyectos de
investigación

6. • Reutilización
• Permisos
• Acceso
abierto
• Códigos de
conducta
• Integridad
• Ética
• Respeto
• Honestidad
• Publicaciones
• Datos
• ……
• Genera nuevos
servicios
basados en
datos abiertos
Infraestructura
Tecnología
Acceso
Compartir
Buenas
prácticas
Factores implicados en la Open Science
6

7. 7
2007-2013
2014-2020

8. http://data.consilium.europa.eu/doc/document/ST-9526-2016-INIT/en/pdf
Science ministers from European
Union nations AGREED last month to
make publicly funded research
publications freely available by 2020.
Each country will implement its own
publication policy.
The Council:
UNDERLINES the principle for the
optimal reuse of research data should
be: “as open as possible, as closed as
necessary”.
EMPHASIZED that the opportunities
for the optimal reuse of research data
can only be realised if data are
consistent with the FAIR principles
(findable, accessible, interoperable
and re-usable) within a secure and
trustworthy environment
8

9. Draft European Open Science
Agenda. 26 February 2016
Based on 5 policy actions:
• Foster Open Science
• Remove barriers to Open Science
• Develop research infrastructures for Open Science
• Mainstream Open Access to research results
• Embed Open Science in Society
https://ec.europa.eu/research/openscience/pdf/draft_european_open_science_agenda.pdf
9

10. https://ec.europa.eu/research
/press/2016/pdf/opendata-
infographic_072016.pdf
10

11. 11

12. Directrices
para
investigadores
*
“Infraestructura”
“Consejo”
12
*http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/
oa_pilot/h2020-hi-oa-pilot-guide_en.pdf

13. “The European Open Science Cloud is a
supporting environment for Open science
and not an ‘open cloud’ for science”
13

14. “GO-FAIR” is a proposal for the
practical implementation of the
European Open Science Cloud
(EOSC) through a federated
approach making optimal use of
existing initiatives and
infrastructures in the participating
Member States
14https://www.dtls.nl/fair-data/go-fair/

15. 15
¿Qué requiere Europa?

16. Horizon2020 (2014-2020)
http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-pilot-
guide_en.pdf
• OA: verde y dorada, cubre todas las áreas
• Nuevas directrices, nuevas cláusulas (29.2 y 29.3)
• Piloto OA para los datos de investigación (cláusula
29.3, para 7 áreas)
• Se insta a los estados miembros a desarrollar políticas
OA +infraestructura
• Embargos: 6 y 12 meses como en el 7FP (vía verde).
Depósito inmediato vía dorada
• Apoyo: OpeAire2020 y Zenodo (admite datasets)
16

17. 17
“Open data and content can be freely
used, modified, and shared by anyone
for any purpose” (The Open Definition
http://opendefinition.org/od/2.1/en/)
https://www.force11.or
g/group/fairgroup/fairpr
inciples
Principios FAIR

18. 18

19. 19

20. Research Data Pilot in H2020
A novelty in Horizon 2020 is the Open
Research Data Pilot which aims to improve
and maximise access to and re-use of
research data generated by projects. The
legal requirements for projects
participating in this pilot are contained in
the optional article 29.3 of the Model
Grant Agreement.
http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_p
ilot/h2020-hi-oa-data-mgt_en.pdf
20

21. For the 2016-2017 Work Programme, the areas of Horizon 2020 participating in the
Open Research Data Pilot are:
• Future & Emerging Technologies
• Research infrastructures
• Leadership in enabling & industrial technologies – Information & Communication
Technologies
• Nanotechnologies, Advanced Materials, Advanced Manufacturing & Processing, &
Biotechnology – 'nanosafety' & 'modelling' topics
• Societal Challenge – Food security, sustainable agriculture & forestry, marine &
maritime & inland water research & the bioeconomy - selected topics as specified
in the work programme
• Societal Challenge – Climate Action, Environment, Resource Efficiency & Raw
Materials – except raw materials
• Societal Challenge – Europe in a changing world – inclusive, innovative &
reflective societies
• Science with & for Society
• Cross-cutting activities – focus areas – part Smart & Sustainable Cities
Los nuevos proyectos concedidos a partir de enero de 2017
entran en el Piloto todas las disciplinas
21

22. References to research data management are included in Article 29.3 of the Model
Grant Agreement (article applied to all projects participating in the Pilot on Open
Research Data in Horizon 2020).
29.3 Open access to research data
[OPTION for actions participating in the open Research Data Pilot: Regarding the
digital research data generated in the action (‘data’), the beneficiaries must:
(a) deposit in a research data repository and take measures to make it possible for
third parties to access, mine, exploit, reproduce and disseminate — free of charge
for any user — the following:
(i) the data, including associated metadata, needed to validate the results
presented in scientific publications as soon as possible;
(ii) other data, including associated metadata, as specified and within the deadlines
laid down in the ‘data management plan’ (see Annex 1);
(b) provide information — via the repository — about tools and instruments at the
disposal of the beneficiaries and necessary for validating the results (and — where
possible — provide the tools and instruments themselves).
https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h
2020-hi-oa-pilot-guide_en.pdf 22

23. Requisitos del Open Data Pilot
• Desarrollar y actualizar un plan de gestión de datos (presentación a los
6 meses, en las posibles evaluaciones intermedias, en el informe final)
• Depósito de los datasets en un repositorio de datos ( ver Registry of
Research Data Repositories http://www.re3data.org/ )
• Facilitar a terceros el acceso, la reutilización, la reproducción y
diseminación de los datos, sin coste para el usuario
• Facilitar la información de las herramientas, métodos o instrumentación
para validar los resultados (o facilitar las herramientas, si fuera
necesario) 23

24. Posibles exenciones del Piloto
• Si los resultados esperados son susceptibles de ser explotados
comercial o industrialmente
• Si existen razones de confidencialidad o de seguridad
• Si la exposición de los datos es incompatible con alguna normativa
referente a la protección de datos personales
• Si la exposición de los datos pone en riesgo el desarrollo del objetivo
principal del proyecto
• Si el proyecto no prevé la generación o colección de datos
• Si existe alguna otra razón legítima para no participar en el Piloto
La exención puede expresarse en la solicitud del proyecto o bien
durante su ejecución, y deben exponerse las razones en el plan de
gestión de datos 24

25. Actions participating in the pilot must draw up a data management plan (DMP) within the
first 6 months of the project implementation.
The data management plan must support the management life-cycle for all data that will be
collected, processed or generated by the action. It must cover how to make data findable,
accessible, interoperable and re-usable (FAIR), including:
• the handling of data during and after the project
• what data will be collected, processed or generated
• what methodology and standards will be applied
• whether data will be shared / made open access (and how) and, if any, what data will
not be shared / made open access (and why)
• how data will be curated and preserved.
The data management plan should be updated (and become more precise) as the project
evolves. New versions should be created whenever important changes to the project occur
(e.g. new data sets, changes in consortium policies, etc), at least as part of the mid-term
review (if any) and at the end of the project.
http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/amga/h20
20-amga_en.pdf 25

26. Univ. Queensland http://guides.library.uq.edu.au/research-data-management
26

27. Diseñar,
planificar
Recolectar,
capturar,
generar
Analizar
Gestionar,
almacenar,
preservar
Compartir,
publicar
Descubrir,
reutilizar,
citar
Ciclo de vida de los datos
Fase I:
“generación”
Fase II:
“reutilización”
Datos de
investigación
27

28. ¿Qué debe contemplar un plan de gestión de datos?
(mínimos)
Las instituciones o agencias financiadoras pueden tener
especificaciones propias
Diseñar,
planificar
Recolectar,
capturar,
generar
Analizar
Gestionar,
almacenar,
preservar
Compartir,
publicar
Descubrir,
reutilizar,
citar
• Descripción de los datos que se van a
tomar o crear
• La metodologia y estándares para la
recolección de datos
• Aspectos éticos y relacionados con la
propiedad intellectual, si corresponde
• Vías para compartir y acceder a los datos
• Estrategia para la preservación de datos
28

29. Herramientas
DMPTOOL has been developed by the
University of California Curation CenterDMP online has been developed by the Digital Curation
Centre (UK) https://dmponline.dcc.ac.uk/
Futuro
RDM Roadmap
29

30. http://www.consorciomadrono.es/pagoda/index2.php
30
https://www.dmptuuli.fi/
Herramientas…….

31. DMP online has been developed by the Digital Curation Centre (UK)
https://dmponline.dcc.ac.uk/
31

32. Example: http://www.dcc.ac.uk/sites/default/files/documents/adocs/Leeds-
RoaDMaP-DMPs.pdf 32

33. Correspondence between Annex 1 from EU and DCC-DMP
33

34. 34

35. 35
http://ec.europa.eu/research/participants/data/ref/h2020/mga/erc/h20
20-mga-erc-multi_en.pdf

36. Resumen
Findable
Accesible
Interoperable
Reusable
Costes de
preservación,
alojamiento…si los
hubiera
Los datos deben
ser “FAIR”
36

37. 37

38. http://www.accesoabierto.info/
38

39. 39

40. 40
Servicios-Europa-Datos

41. 41
Servicios de apoyo a los investigadores ….

42. 42
https://www.openaire.eu/intro-researchers

43. OpenAIRE’s e-infrastructure Commons
43
Publications
repositories
Research
Data
repositories
CRIS
systems
Registries
(e.g. projects)
OA
Journals
Software
Repositories
Validation
Cleaning De-
duplication
Enrichment
By inference
Funders, research admins,
research communities
• Research impact
• Research trends
• Open Access trends
Content providers
• Repository validation
• Repository notification broker
• Repository analytics and usage stats
Researchers
• Claim publications, datasets, software
• Deposit publications, datasets, software
• Search & browse: interlinked
publications, datasets, projects
• Open Access & DMP Helpdesk
• End-User feedback
Content Providers
Info Space Services
End-User Services
Proje
ct
initiat
ive
Fund
er
Fundi
ng
Resul
t
Public
ation
Data
Softw
are
Organiz
ation
GUIDE
LINES
TERMS
OF USE

44. 44

45. 45
http://eoscpilot.eu/science-demonstrators
Objetivo: mostrar la relevancia y utilidad de los
servicios de la EOSC que faciliten la reutilización de los
datos y contribuir al desarrollo de la EOSC

46. 46

47. 47
http://ec.europa.eu/research/openscience/index.cfm?pg=home&section=monitor

48. 48

49. 49
Algunos retos

50. http://www.eua.be/Libraries/publications-homepage-list/oa-survey-2015-2016-results.PDF
N=169, 33 Países 2015-enero 2016
50

51. The reasons indicated for a lack of formal or informal
policies/guidelines on Open Access to data included the following:
• Novelty of the topic (“just started to think about this”)
• Priority given implementing institutional policy on Open Access to research publications
• Complexity of the topic
• Technical complexity in implementing Open Access to research data (e.g. variety of
research fields in institution, multiple data formats)
• Low interest levels from researchers
• General lack of awareness on the topic
• Absence of national guidelines or mandate/policies by research funders
• Lack of expertise on the topic at institutional level
• Lack of infrastructure or absence of funds to develop the needed infrastructure
• Unclear legal frameworks/no legislation
• Unclear distribution of responsibility on this issue between researchers, departments,
libraries and funders
• Lack of institutional coordination among the different stakeholders (researchers,
departments, libraries, funders)
• Institutional profile based on strong cooperation with companies makes this issue hard
to deal with (e.g. IPR)
• “Scepticism about the benefit of Open Access”
51

52. http://www.eua.be/Libraries/publications-homepage-list/towards-full-open-access-in-2020-aims-and-
recommendations-for-university-leaders-and-national-rectors-conferences.pdf
Institutions need to increase their capacity in the areas of
research data management and Text and Data Mining (TDM)
practices, including, in particular, articles and e-books.
• Establish an institutional policy with clear guidelines for the
management of research data (validation, preservation, curation,
availability), adopting the set of guiding principles to make data
Findable, Accessible, Interoperable, and Re-usable (FAIR) and make
them part of the European Open Science Cloud (EOSC).
• Make metadata publicly available when data must be closed due
to its nature or for reasons of confidentiality or security.
• Develop institutional capacity in the field of research data
management (e.g. improving technical and legal expertise,
developing skills in data management and in Text and Data
Mining (TDM).
• Provide legal advice, training and incentives for researchers to
deposit their data and develop TDM practices
52

53. Acciones en favor del OA a los datos de investigación (extracto del informe anterior)
Directrices
infraestructuras
Políticas
Reconocimiento Colaboración
Formación Concienciación
Incentivación
http://eoscpilot.eu/about/eoscpilot-brief
https://cdn1.euraxess.org/sites/default/files/policy_library/ec-rtd_os_skills_report_final_complete_2207_1.pdf
53

54. http://ec.europa.eu/research/openscienc
e/pdf/os_rewards_wgreport_final.pdf
54

55. Los datos una oportunidad…
http://edison-project.eu/sites/edison-project.eu/files/filefield_paths/edison_cf-ds-release2-
Data Science competence groups for
business oriented profiles.
Science competence groups for general or
research oriented profiles
55

56. ¡Gracias!
rmelero@iata.csic.es
¿?¿?¿?
???
¡?
56