EDBT 2026 Demo / reviewers in the wild / expert
Dave Feenan
dblp:339/8415
· DBLP profile ↗
2ranked-venue papers in the field
0as first author
2since 2021 · last 2022
—ORCID · none
Domains — venue-derived; a paper can count in several
Big Data, Cloud & Distributed Data Systems · 2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Smardy: Zero-Trust FAIR Marketplace for Research DataabstractOver the past five years, different organisations have increasingly called for science to become more open and reproducible. They have endorsed a set of data-management principles known as the FAIR (Findable, Accessible, Interoperable, Reusable) principles. As such, there is a growing trend towards the open availability of research data, as researchers continue to enhance reproducibility by enabling sharing and opening of their findings and datasets. However, there is not yet a standardised way to openly enable access to datasets while keeping control of their final use, potentially obtaining benefits from their utilisation. This paper introduces Smardy, an EU-funded project which is deploying a traceable FAIR-compliant open innovation marketplace for data. Its innovative method for data exchange consists of the use of blockchain for controlling access rights to data, with data models able to grant access according to policies completely kept under the control of the data owner/producer. We also describe how Smardy employs dimensionality reduction techniques to automatically generate FAIR–compliant metadata, statistical fingerprinting to identify derivated datasets, and watermarking to help data owners trace the distribution of multiple copies of a dataset. Ion-Dorinel Filip, Cosmin Ionite, Alba González-Cebrián, Mihaela Balanescu, Ciprian Dobre, Adriana E. Chis, Dave Feenan, Adrian-Alexandru Buga, Ioan-Mihai Constantin, George Suciu, George V. Iordache, Horacio González-Vélez |
IEEE Big Data | 7 |
| 2022 | Open Science and Research Data Management: A FAIR European Postgraduate ProgrammeabstractOpen Science is widely regarded as a culture that is characterised by the transparency and broad accessibility of scholarly work, where researchers share openly artefacts almost immediately and with a very wide audience. The overarching aim of this paper is to document the systematic development of a European postgraduate programme on Open Science and Research Data Management developed by the TRAINRDM project. TRAINRDM is a 30-month European Union funded project, which aims to develop a training network around Open Science and Research Data Management. We have applied a comprehensive survey collecting 239 responses from researchers across Europe, representative of 2.58 million individuals i.e. the total number of researchers employed in the EU-27 region. We then mapped out existing skills and offerings at different TRAINRDM partner institutions to produce a fully-online postgraduate programme with micro-credentials, fully distributed delivery, and compliance to FAIR principles to address academic and industrial research needs. The main outputs of the project are a training programme for Early Career Researchers delivered in Summer 2022, and a the postgraduate programme (Master degree) to be fully validated under the European Qualifications Framework at Level 7 and delivered in 2023. The TRAINRDM curricula, teaching materials, data, and software are openly released under CC BY 4.0 and GPL licenses. Horacio González-Vélez, Ciprian Dobre, Barbara Sánchez Solís, Giulia Antinucci, Dave Feenan, Dana Gheorghe |
IEEE Big Data | 5 |