Open Science: What, why, how?
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The document outlines the concept of open science, emphasizing its tools and principles aimed at promoting transparency, reproducibility, and collaborative research. It discusses the European Open Science agenda, which includes policies to facilitate open access and data sharing, as well as the Open Research Data Pilot under Horizon 2020 aimed at enhancing access to research data. Additionally, it highlights the importance of fair data principles and the role of various stakeholders in implementing open science initiatives across Europe.
Open Science: What, why, how?
- 1. Open Science: What, why, how? Remedios Melero Consejo Superior de Investigaciones Científicas (CSIC), FOSTER partner Obra licenciada con Creative Commons By 4.0 internacional
- 3. https://www.fosteropenscience.eu/ Diagram of Foster’s Content Classification 3
- 4. 4 Open science is beyond open access
- 6. “Open Science (OS) offers researchers tools and workflows for transparency, reproducibility, dissemination and transfer of new knowledge” “The conduction of science in a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, with terms that allow reuse, redistribution and reproduction of the research. ( Open science, http://en.wikipedia.org/wiki/Open_science) “Open science is the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.” (Michael Nielsen, http://openscienceasap.org/open-science/ ) 6 Significado de la Open Science
- 7. Principios de la Open Science Open Methodology (Métodos, procesos, documentos relevantes) Open Source (Soft- y Hardware) Open Data ( datos reutilizables) Open Access to scholarly outputs (acceso gratis y libre) Open Peer Review (transparencia en la evaluación y en los criterios de calidad) Open Educational Resources (MOOCs, OERs) http://openscienceasap.org/open-science/
- 8. Open access…( término definido por primera vez en la Declaración de Budapest, febrero 2002) “Los recursos en acceso abierto son digitales, online, libres de cargas económicas, libres de la mayor parte de restricciones debidas a los derechos de explotación” (Peter Suber) Objetos digitales de acceso abierto: • Acceso gratuito online (libre de barreras económicas) • Eliminan ± restricciones de copyright (permite la reutilización de acuerdo a los permisos o licencias que se establezcan) 8
- 10. Consecuencias/beneficios del acceso abierto Visibilidad “Impacto” Impacto social TendenciasResponsabilidad Retorno de inversión Rompe barreras
- 13. Accessible Data must be located in such a manner that it can readily be found and in a form that can be used. Useable In a format where others can use the data or information. Data should be able to be reused, often for different purposes, and therefore will require proper background information and metadata. Assessable In a state in which judgments can be made as to the data or information’s reliability. Intelligible Comprehensive for those who wish to scrutinise something. Open data must be accessible, useable, assessable and intelligible ( extracted from Science as an Open Enterprise, 2012 )
- 14. FAIR Data Principles: • Findable • Accessible • Interoperable • Re-usable
- 15. Australian National Data Service. http://www.ands.org.au/cite-data/index.html Identification of datasets favours their use and citation Data can be cited….
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- 21. Europa vs Open science…..
- 29. 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 29
- 30. 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 Projects in other areas can participate on a voluntary basis 30
- 31. Opting out partially or entirely from the Pilot on Open Research Data Projects can opt out at any stage if: • Participation is incompatible with the Horizon 2020 obligation to protect • Results that can reasonably be expected to be commercially or industrially exploited • Participation is incompatible with the need for confidentiality in connection with security issues • Participation is incompatible with rules on protecting personal data • Participation would mean that the project's main aim might not be achieved • The project will not generate / collect any research data • There are other legitimate reasons not to take part in the Pilot (at proposal stage - free text box provided). 31
- 32. Types of data covered by the Open Research Data Pilot: 1. The data, including associated metadata (i.e. metadata describing the research data deposited), needed to validate the results presented in scientific publications as soon as possible ("underlying data") 2. Other data (for instance curated data not directly attributable to a publication, or raw data), including associated metadata, as specified and within the deadlines laid down in the data management plan that is, according to the individual judgement by each project In a research context, examples of data include statistics, results of experiments, measurements, observations resulting from fieldwork, survey results, interview recordings and images. The focus is on research data that is available in digital form. 32
- 33. 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 33
- 34. Projects participating in the pilot will be required to develop a Data Management plan (DMP), in which they will specify what data will be open. • The Commission does NOT require applicants to submit a DMP at the proposal stage. • A DMP is therefore NOT part of the evaluation. • DMPs are a deliverable for those participating in the pilot (within first 6 months, at midterm and at the end of the project- at least) 34
- 36. 36 From vision to action
- 37. 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 37
- 38. Draft European Open Science Agenda. 26 February 2016 Some actions… • Reward researchers engaged in Open Science activities (career development) • Allow research funders to provide specific incentives for 'collaborative science‘ including societal actors and citizen science • Improve expertise and guidance (In open science) • Implement data-sharing principles (e.g. G8 principles / FAIR) • Recognize new professions e.g. Establish a professorship on Openness, on Big data • management, data mining etc. • Introduce openness as criterion for receiving research funding • Analyse current competency levels (research organisations) • Adapt university curricula to new needs • Pilot a EU Certificate of Open Research • Create incentives for skill transfer in data analytics and cloud technology for research Some implementations…. 38
- 39. This document is a living document reflecting the present state of open science evolution. It is based on the input of many participating experts and stakeholders of the Amsterdam Conference ‘Open Science – From Vision to Action’, hosted by the Netherlands’ EU Presidency on 4 and 5 April 2016. Formulated to reach two important pan-European goals for 2020: 1. Full open access for all scientific publications 2. A fundamentally new approach towards optimal reuse of research data To reach these goals by 2020 we need flanking policy: • New assessment, reward and evaluation systems • Alignment of policies and exchange of best practices http://english.eu2016.nl/documents/reports/2016/04/04/amsterdam-call-for-action-on- open-science 39
- 40. Removing barriers to open science 1. Change assessment, evaluation and reward systems in science 2. Facilitate text and data mining of content 3. Improve insight into IPR and issues such as privacy 4. Create transparency on the costs and conditions of academic communication Developing research infrastructures 5. Introduce FAIR and secure data principles 6. Set up common e-infrastructures Fostering and creating incentives for open science 7. Adopt open access principles 8. Stimulate new publishing models for knowledge transfer 9. Stimulate evidence-based research on innovations in open science Mainstreaming and further promoting open science policies 10. Develop, implement, monitor and refine open access plans Stimulating and embedding open science in science and society 11. Involve researchers and new users in open science 12. Encourage stakeholders to share expertise and information on open science Twelve actions grouped around the five cuttig themes that follow the structure of the European Open Science Agenda proposed by the EC 40
- 41. Datos sobre autores vs acceso abierto y datos
- 42. 42 Researchers’ green open access practice: a cross-disciplinary analysis. Spezi et al., 2013 (https://dspace.lboro.ac.uk/dspace-jspui/handle/2134/12324). Some results from the EC-funded Publishing and the Ecology of European Research (PEER) project (http://www.peerproject.eu/) Motivaciones para el depósito por tipo de repositorio
- 43. 43 Quién hace el depósito en repositorios institucionales Quién hace el depósito en repositorios temáticos
- 44. UNESCO (2012), Policy Guidelines for the Development and Promotion of Open Access, UNESCO Publishing, and Björk et al. (2010), “Open Access to the scientific journal literature: Situation 2009”, PloS ONE, Vol. 5, No. 6. La disciplina importa….
- 45. De dónde obtiene el trabajo. Preliminary analysis of OECD NESTI Pilot Survey of Scientific Authors 2014-15. Note: NK = not known.
- 47. Ventajas del OA
- 49. Factors not to upload your article
- 50. Encuesta de la EUA entre universidades europeas (106 univ. de 30 países hecha en 2014).
- 51. http://exchanges.wiley.com/blog/wp-content/uploads/2014/11/Researcher-Data-Insights- Infographic-FINAL-REVISED-2.jpg Standard practice, increase impact and public benefit
- 53. The purpose of LEARN is to take the LERU Roadmap for Research Data produced by the League of European Research Universities (LERU) and to develop this in order to build a coordinated e-infrastructure across Europe and beyond. LEARN will deliver: • a model Research Data Management (RDM) policy; • a Toolkit to support implementation, and; • an Executive Briefing in five core languages so as to ensure wide outreach. http://learn-rdm.eu 53
- 54. Project Outputs 1) An analytic rubric to standardize the review of data management plans as a means to inform targeted expansion or development of research data services at academic libraries; 2) A study utilizing the rubric that presents the results of data management plan analyses at five universities. 54
- 55. http://edison-project.eu/ Data Scientist is a complex profession ..”data scientists range from pure e-Science driven by research communities, to applications of Data Science Professionals in Public Institutions” “future Data Scientists must posses knowledge (and obtain competencies and skills) in data mining and analytics, information visualisation and communication, as well as in statistics, engineering and computer science, and acquire experiences in the specific research or industry domain of their future work and specialisation. 55
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