(A.) Policy and legislation
(A.1) Policy objectives
Research data and computing infrastructures fostering a paradigm shift in science (digital science/eScience).
The emergence of data driven science reflects the increasing value of a range of observational, sensor, simulation, streaming and experimental data in every field of science. Data e-Infrastructures link knowledge territories, which blur geographical and disciplinary boundaries.
The present European and global research data landscape is highly fragmented, by disciplines or by domains (oceanography, life sciences, health, agriculture, space, climate, etc.). A variety of institutions, some national, some international, strive to deal with some aspects of data, but there is no effort to seek or achieve some degree of coherence.
Some research domains are experiencing exponential growth in data produced with the rate doubling in a timeframe that can be as short as a few months (seven months in the case of second generation sequencing of genes), while others plan new instruments that will suddenly produce enormous amounts of data.
To create a competitive European research area, Europe has already invested a significant amount of resources into modernising the European landscape of research infrastructures and facilities of excellence.
The ESFRI roadmap stretches across a range of scientific disciplines in different European nations and includes recommendations for a suite of ambitious initiatives in areas such as biological and medical sciences, environment, social sciences and humanities, geophysics and astronomy, physical and engineering.
Underpinning the efforts of the research communities, e-infrastructures foster innovation and scientific progress across disciplines and between the private and public sector. A large number of data e-Infrastructures, mixing the capabilities of scientific communities and technology providers, have been launched in domains of astronomy, earth and ocean observation, climate, environment and biodiversity, etc. Moreover, pan European e-Infrastructures initiatives were launched across disciplinary domains providing a participatory network of open access repositories at European scale. These initiatives fill the gap between user-application and generic e-Infrastructure layers for high-volume storage, data interoperability, high-performance computing and connectivity layers.
Building on these existing EU-funded e-Infrastructures, the European Open Science Cloud and the European Data Infrastructure, as presented in the Communication “European Cloud Initiative”, will consolidate the efforts to accelerate and support the transition to more effective open science and open innovation in the digital single market. In this context, the implementation of standards and recommendations will be of utmost importance in order to allow for interoperability, avoid fragmentation and improve the efficiency and effectiveness of research by optimizing resources and encouraging economies of scale. The European Cloud Initiative will provide European science, industry and public authorities with world-class data infrastructures, high-speed connectivity and increasingly powerful high performance computers. It will make it easier for researchers, businesses and public services to fully exploit the benefits of big data by making it possible to move, share, re-use and process data seamlessly across global markets and borders, and among institutions and research disciplines.
The initiative will establish the European Open Science Cloud (EOSC) as a virtual environment to store and process large volumes of information generated by the big data revolution. This will be supported by the European Data Infrastructure (EDI), deploying the high-bandwidth networks and the supercomputing capacity necessary to access and process large datasets stored in the cloud.
Both the EOSC and the EDI will build on existing EU-funded e-infrastructures and will bring networking, data and computing services closer to European researchers and innovators.
(A.2) EC perspective and progress report
Research/science funders have a common problem when tackling the area of research data infrastructure. The landscape is geographically fragmented and different disciplines have different practices. It is difficult to build critical mass and provide common services to different scientific disciplines and to take advantage of economies of scale. Some scientific communities are pushing the envelope and adopting new technologies while others are lagging behind. Scientists are, at the end of the day, the generators and users of research data in their experiments, simulations, visualization of complex data arrays, etc. There is a need to bring together capabilities from different scientific fields and also the competences of technology and service providers to use the potential of ICT.
Interoperable data infrastructures will allow researchers and practitioners from different disciplines to access and process the data they need in a timely manner. They can collaborate across different domains of science and engineering. The innovative power of industry and enterprise will be used trough by clear and efficient arrangements for data exchange between private and public sectors.
Today, EU-funded e-Infrastructures play a fundamental role in the life of European researchers and innovators. E-Infrastructure projects funded under the Horizon 2020 work programme 2014-2015 and 2016-2017 are helping researchers tackle the challenges posed by one specific societal challenge.
(A.3) References
- COM(2016) 178 European Cloud Initiative — Building a competitive data and knowledge economy in Europe
- COM(2016) 180 Digitising European Industry - Reaping the full benefits of a Digital Single Market.
- COM(2016) 176 ICT Standardisation Priorities for the Digital Single Market.
- COM(2012) 401 Towards better access to scientific information: Boosting the benefits of public investments in research.
- COM(2012) 4890 Commission Recommendation on access to and preservation of scientific information.
(B.) Requested actions
EU funded projects and initiatives are actively working with recommendations, models and standards. An example of this could be the work of OpenAIRE and EuroCRIS initiatives to expand the CERIF model to also include research outputs. CERIF was initially conceived to document and exchange research information (funding programmes and projects, researchers and research institutions, etc.) and has since been adopted by many Member States and institutions.
Moreover, the Research Data Alliance has been approached and has engaged in the process of identifying Technical Specifications as ICT specifications for public procurement within the EU. These might come from existing initiatives in specific research fields or from established general purpose initiatives.
Action 1 SDOs to work closely with service providers, RDA and other similar initiatives on identifying standards needs and developing them in the area of research data in the context of the European Open Science Cloud.
(C.) Activities and additional information
(C.1) Related standardisation activities
The Research Data Alliance (RDA) is not primarily a standardisation body but is a mechanism to speed-up the adoption of standards for research data and computing infrastructures. The RDA also provides some technical specification and the Commission with the advice of the Multi-Stakeholder Platform on ICT standardisation has identified a number of RDA Technical Specifications as ICT specifications for public procurement within the EU.
In order to facilitate and improve the process of developing recommendations that are relevant and have the potential of becoming ICT specifications, there is an ongoing effort of promoting industrial participation within the RDA processes.
Research Data Alliance (RDA)
Supports the Commission’s strategy to achieve global scientific data interoperability in a way that real actors (users and producers of data, service providers, network and computing infrastructures, researchers and their organisations) are in the driving seat. It has memorandums of understanding (MoUs) with related standardisation activities/organisations: IETF, W3C, ICSU/CODATA. Synergies with other organisations/activities will need to be identified in the future.
ITU-T
Regarding the global e-Infrastructure, the ITU is using the digital object architecture (DOA), on which the recommendation ITU-T X.1255 “Framework for discovery of identity management information” is based.
SG11 is studying the global problem of combating counterfeiting. Within this activity, SG11 developed the Technical Report on Counterfeit ICT Equipment, Survey report on counterfeit ICT devices in Africa region and Technical Report on Reliability of IMEI. SG11 also approved Recommendation ITU-T Q.5050 “Framework for solution to combat counterfeit ICT Devices” and Recommendation ITU-T Q.5052 “Addressing mobile devices with duplicate unique identifier”.
SG11 has a mandate to study issues related to combating stolen ICT equipment. SG11 approved Recommendation ITU-T “Framework for Combating the use of Stolen Mobile ICT Devices”.
SG20 approved Recommendation ITU-T Y.4808 “Digital entity architecture framework to combat counterfeiting in IoT”. The intent of this Recommendation is to provide solutions to deter the spread of counterfeit IoT devices worldwide.
SG13 approved new standards on trust for ICT infrastructures and services:
- Recommendation ITU-T Y.3051 “The basic principles of trusted environment in ICT infrastructure” provides the definition, common requirements and the basic principles of creating trusted environment.
- Recommendation ITU-T Y.3052 “Overview of trust provisioning for information and communication technology infrastructures and services” describes the key characteristics of trust. In addition, the trust relationship model and trust evaluation based on the conceptual model of trust provisioning are introduced.
- Recommendation ITU-T Y.3053 “Framework of trustworthy networking with trust-centric network domains”
- SG13 continue working on the attributes that can represent trustworthiness, which can be applied to ICT infrastructures and services. There are several on-going work on architecture for trust enabled service provisioning, trust index to evaluate and quantify trustworthiness for ICT infrastructures and servicesetc. From the perspectives of standardisation, trust should be quantitatively and/or qualitatively calculated and measured, which is used to evaluate the values of physical components, value-chains among multiple stakeholders, and human behaviors including decision making
- FG NET2030 technical report “Network 2030- Additional representative use cases and key network requirements for Network 2030” deals with the key network requirements for huge scientific data applications (astronomical telescopes) and accelerators (Large Hadron Collider).http://itu.int/ITU-T/go/sg13
Other activities related to standardisation
Related topics in H2020 WP on research infrastructures including e-Infrastructures (proposals selected within these calls may contribute to standardisation):
EINFRA-1-2014:
Managing, preserving and computing with big research data
EINFRA-3-2014:
Towards global data e-Infrastructures — research data alliance
EINFRA-8-2014:
Research and education networking — GÉANT
INFRASUPP-7-2014:
e-Infrastructure policy development and international cooperation
EINFRA-22-2016:
User driven e-infrastructure innovation
EINFRA-21-2017:
Platform-driven e-infrastructure innovation
EINFRA-12-2017:
Data and Distributed Computing e-Infrastructure for Open Science
INFRASUPP-02-2017:
Policy and International cooperation measures for research infrastructures (RDA)
(C.2) additional information
RDA will be a good support to turn the proposed framework for action for data infrastructures into practice. The Commission run a public consultation on the key priority areas for H2020 on data Infrastructures which received an excellent feedback. Stakeholders are motivated and, above all, ready to come together and turn the identified priorities into real action. Europe will consolidate its role of a global partner and a global leader in research data infrastructures.