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Europa requisitos y servicios en torno a los datos de investigacion

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

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Europa requisitos y servicios en torno a los datos de investigacion

  1. 1. Europa: requisitos y servicios en torno a los datos de investigación Remedios Melero (IATA –CSIC) rmelero@iata.csic.es 1
  2. 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. 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. 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. 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. 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. 7 2007-2013 2014-2020
  8. 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. 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. 10. https://ec.europa.eu/research /press/2016/pdf/opendata- infographic_072016.pdf 10
  11. 11. 11
  12. 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. 13. “The European Open Science Cloud is a supporting environment for Open science and not an ‘open cloud’ for science” 13
  14. 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. 15 ¿Qué requiere Europa?
  16. 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. 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. 18
  19. 19. 19
  20. 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. 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. 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. 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. 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. 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. 26. Univ. Queensland http://guides.library.uq.edu.au/research-data-management 26
  27. 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. 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. 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. 30. http://www.consorciomadrono.es/pagoda/index2.php 30 https://www.dmptuuli.fi/ Herramientas…….
  31. 31. DMP online has been developed by the Digital Curation Centre (UK) https://dmponline.dcc.ac.uk/ 31
  32. 32. Example: http://www.dcc.ac.uk/sites/default/files/documents/adocs/Leeds- RoaDMaP-DMPs.pdf 32
  33. 33. Correspondence between Annex 1 from EU and DCC-DMP 33
  34. 34. 34
  35. 35. 35 http://ec.europa.eu/research/participants/data/ref/h2020/mga/erc/h20 20-mga-erc-multi_en.pdf
  36. 36. Resumen Findable Accesible Interoperable Reusable Costes de preservación, alojamiento…si los hubiera Los datos deben ser “FAIR” 36
  37. 37. 37
  38. 38. http://www.accesoabierto.info/ 38
  39. 39. 39
  40. 40. 40 Servicios-Europa-Datos
  41. 41. 41 Servicios de apoyo a los investigadores ….
  42. 42. 42 https://www.openaire.eu/intro-researchers
  43. 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. 44
  45. 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. 46
  47. 47. 47 http://ec.europa.eu/research/openscience/index.cfm?pg=home&section=monitor
  48. 48. 48
  49. 49. 49 Algunos retos
  50. 50. http://www.eua.be/Libraries/publications-homepage-list/oa-survey-2015-2016-results.PDF N=169, 33 Países 2015-enero 2016 50
  51. 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. 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. 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. 54. http://ec.europa.eu/research/openscienc e/pdf/os_rewards_wgreport_final.pdf 54
  55. 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. 56. ¡Gracias! rmelero@iata.csic.es ¿?¿?¿? ??? ¡? 56

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