Workshop: Perspectives in understanding open access to research data infrastructure and technology challenges

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1 Workshop: Perspectives in understanding open access to research data infrastructure and technology challenges Key findings on technological barriers, solutions and best practice Lorenzo Bigagli CNR-IIA /

2 Outline Introduction RECODE activity summary The GEOSS lesson Scope Key findings Online questionnaire, case studies interviews, literature review Overview on Infrastructure and Technology challenges Questions & Answers

3 Activity Summary What Infrastructure and technology challenges on Open Access to Research Data When February 2014 (Report) Who Coordinated by CNR-IIA Contributions by AUP, BTH, USFD How Online questionnaire, case studies interviews, literature review, workshop, Advisory Board comments

4 Case Studies Physics Health Bioengineering Earth Sciences Archaeology Particle Physics and Particle Astrophysics (PPPA) Group FP7 Project EVA (Markers for emphysema versus airway disease in COPD) Bioengineering Institute, Auckland NZ, and Virtual Physiological Human (VPH) Community Global Earth Observation System of Systems (GEOSS) Open Context

5 The GEOSS lesson Global Earth Observation System of Systems EuroGEOSS EGIDA Coordinating Earth and Environmental cross-disciplinary projects to promote GEOSS EGIDA Methodology

6 EGIDA Methodology General approach for (re-) engineering national Science & Technology infrastructures for a sustainable contribution to GEOSS System of Systems (SoS) approach Mobilization of resources made available by national, European and global initiatives

7 EGIDA - barriers to information sharing Behavioural Technical Economical Legal Interoperability issues Functional gaps Lack of expertise Communication issues

8 Scope definitions Infrastructure includes Technological assets (hardware and software) Personnel involved All the procedures for management, training and support continuous operation and evolution Technical barriers are not related to the will or permission to share resources, but to the capability of doing it Stakeholders may be willing and authorized to share resources, but unable to do it [EGIDA Methodology]

9 Scope stakeholders The existence and nature of obstacles to data sharing can be discovered and analyzed through surveys and interviews Members of the Stakeholders Network can provide information about behavioral, legal, technical and financial barriers to data sharing [EGIDA Methodology, Guideline TA.2.1] Based on Deliverable D1.1 by WP1 (Stakeholder Values and Ecosystems) Aligned with taxonomy by WP6 (Stakeholder Engagement and Mobilisation)

10 WP6 Stakeholder Functional Taxonomy We congregate the disseminator and curator roles We assume they share similar concerns for our purpose Citizens may be considered as research data user/producers (cf. Citizen Science) We assume their involvement in use and production of data is mediated by appropriate applications (e.g. mobile apps) that practically isolate them from the implied technological and infrastructural issues

11 Our Stakeholder Perspectives Producers of research data E.g. researchers elaborating raw data Data disseminators/curators In charge of the distribution infrastructure (information systems, e-infrastructure) for storage, access, and maintenance of data E.g. publisher, librarian Funders Providing financial and policy support to research End users of research data at large Including researchers, the industry, governmental agencies, etc.

12 Online questionnaire Closed, concise questions ~50 responses so far Still open

13 Online questionnaire

14 Online questionnaire

15 Online questionnaire

16 Online questionnaire

17 Online questionnaire

18 Online questionnaire

19 Online questionnaire

20 Online questionnaire

21 Online questionnaire

22 Interviews Experience with OA publications, but not with data publications or data preservation Data management plans are being developed, but still at an early stage Solutions for data management and preservation are not common nor centralized Metadata are considered crucial to enable retrieval, reuse and preservation of research data Financial and legal barriers are considered higher priority then technical ones

23 Technology and literature survey Obviously technical barriers are removed through the availability of technical expertise and tools These include the establishment of technical Task Forces, and training activities for individual capacity building, such as workshops, summer schools, web lectures, etc. The infrastructure should be conceived as a System-of Systems to build on the existing and protect previous investments The System-of-Systems Engineering (SOSE) approach is adopted in the main international initiatives on data sharing including GEOSS [EGIDA Methodology]

24 EC Public Consultation on Open Research Data 2 nd July 2013, in Brussels ~130 attendants stakeholders from the research community, industry, funders, libraries, publishers, infrastructure developers, etc. Focused on five questions How can we define research data and what types of research data should be open? When and how does openness need to be limited? How should the issue of data re-use be addressed? Where should research data be stored and made accessible? How can we enhance data awareness and a culture of sharing?

25 EC Public Consultation on Open Research Data How can we define research data and what types of research data should be open? Definitions vary, with some contributions defining research data as potentially all data (including public sector information), and some limiting it to data that is the product of research For researchers, research data includes all data from an experiment, study or measurement, including metadata and details on processing data For publishers, data linked to publications is part of the publication

26 EC Public Consultation on Open Research Data How should the issue of data re-use be addressed? Discussions about licensing, but also about technical aspects of open research data Not just on whether and how data should be re-used, but also on the adequacy of e-infrastructures for data re-use Directive on the re-use of public sector information (2003/98/EC, currently under revision) was mentioned several times While public sector information (PSI) is distinct from research data and governed by a specific directive, it is important to remember that this type of information can also be useful for research

27 EC Public Consultation on Open Research Data Where should research data be stored and made accessible? The need for improved data management practices and better data accessibility is a key concern Issues closely linked with data preservation and sustainability of data repositories The readiness of professionals to engage in data curation was also highlighted All stakeholders agreed that any funding body policy on open research data must call on researchers to take the issue of data management seriously by developing data management plans (DMPs) for their research projects

28 H2020 Pilot on Open Access to Research Data Requirements Detailed data management plan covering individual datasets (within 6 months) Deposit the research data, preferably into a research data repository Take measures to enable for third parties to access, mine, exploit, reproduce and disseminate (free of charge for any user) this research data E.g., Creative Commons License (CC-BY, CC0) Provide information about tools and instruments at the disposal of the beneficiaries and necessary for validating the results E.g., specialized software, algorithms, analysis protocols. Where possible, they should provide the tools and instruments themselves

29 H2020 Guidelines on Data Management Scientific research data should be easily Discoverable Accessible Assessable and intelligible Useable beyond the original purpose for which it was collected Interoperable to specific quality standards

30 Big Data The Big Data issue (the 4 V s) Volume - data at rest Velocity - data in motion (streaming) Variety - many types, forms and structures or no structures Veracity - trustworthiness, provenance, lineage, quality Validity - data that is correct Visualization - data in patterns Vulnerability - data at risk Value - data that is meaningful

31 Infrastructure and Technology challenges Overview Heterogeneity standardization, semantics Sustainability Creator Disseminator / Curator interoperability, reuse, organizational arrangements, i18n obsolescence, persistence (PID), preservation, reuse Volume bandwidth bandwidth, storage, scalability (data deluge) Quality Security description, training, fitness for use authorization, licensing description, completeness, peer review Funder preservation, persistence, energy footprint scalability certification End user discoverability, accessibility, usability obsolescence discoverability, accessibility, bandwidth description, peer review, fitness for use accounting licensing authentication, privacy, trust

32 Workshop Questions Where should open research data be stored and made accessible? How can we mitigate the technological barriers to Open Access to research Data? How can we cope with technological sustainability and obsolescence? What emerging technologies could be optimized to promote ease of deposit and retrieval of research data?

33 Workshop: Perspectives in understanding open access to research data infrastructure and technology challenges Key findings on technological barriers, solutions and best practice / Lorenzo Bigagli CNR-IIA

34 EXTRA SLIDES

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