Name
Abstract | ||
|---|---|---|
Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and resources in a way compliant with the FAIR principles and sustain the development of key infrastructure and tools. This paper provides an account of the challenges, experiences and solutions involved in the adoption of FAIR around research objects over several Earth Science disciplines. During this journey, our work has been comprehensive, with outcomes including: an extended research object model adapted to the needs of earth scientists; the provisioning of digital object identifiers (DOI) to enable persistent identification and to give due credit to authors; the generation of content-based, semantically rich, research object metadata through natural language processing, enhancing visibility and reuse through recommendation systems and third-party search engines; and various types of checklists that provide a compact representation of research object quality as a key enabler of scientific reuse. All these results have been integrated in ROHub, a platform that provides research object management functionality to a wealth of applications and interfaces across different scientific communities. To monitor and quantify the community uptake of research objects, we have defined indicators and obtained measures via ROHub that are also discussed herein. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.future.2019.03.046 | Future Generation Computer Systems |
Keywords | Field | DocType |
FAIR principles,Research objects,Research infrastructure,Semantic technologies,Earth Science | Recommender system,Metadata,Enabling,Visibility,Identifier,Reuse,Computer science,Provisioning,Earth science,Digital object | Journal |
Volume | ISSN | Citations |
98 | 0167-739X | 1 |
PageRank | References | Authors |
0.36 | 1 | 27 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrés García-Silva | 1 | 1 | 0.36 |
| José Manuél Gómez-Pérez | 2 | 64 | 12.10 |
| Raúl Palma | 3 | 111 | 10.78 |
| Marcin Krystek | 4 | 1 | 0.36 |
| Simone Mantovani | 5 | 28 | 3.77 |
| Federica Foglini | 6 | 2 | 1.07 |
| Valentina Dal Grande | 7 | 4 | 1.78 |
| Francesco De Leo | 8 | 1 | 0.36 |
| Stefano Salvi | 9 | 13 | 4.55 |
| Elisa Trasatti | 10 | 12 | 3.34 |
| Vito Romaniello | 11 | 1 | 1.72 |
| Mirko Albani | 12 | 3 | 1.21 |
| Cristiano Silvagni | 13 | 1 | 0.36 |
| Rosemarie Leone | 14 | 1 | 0.36 |
| Fulvio Marelli | 15 | 1 | 0.36 |
| Sergio Albani | 16 | 1 | 0.36 |
| Michele Lazzarini | 17 | 1 | 0.36 |
| Hazel J. Napier | 18 | 1 | 0.36 |
| Helen M. Glaves | 19 | 1 | 0.36 |
| Timothy Aldridge | 20 | 1 | 0.36 |
| Charles Meertens | 21 | 1 | 0.36 |
| Fran Boler | 22 | 1 | 0.36 |
| Henry W. Loescher | 23 | 1 | 0.36 |
| Christine Laney | 24 | 1 | 0.70 |
| Melissa A. Genazzio | 25 | 1 | 0.36 |
| Daniel Crawl | 26 | 243 | 21.02 |
| Ilkay Altintas | 27 | 1191 | 106.09 |