Ajit Singh
Enabling Researchers to Make their Data Count
Buch
Research Paper (postgraduate) from the year 2019 in the subject Computer Science - Software, , course: MCA, language: English, abstract: In this paper, I describe the outcomes of the work of the Scholarly Link Exchange (Scholix) working group and the Data Usage Metrics working group. The Scholix working group developed a framework that allows organizations to expose and discover links between articles and datasets, thereby providing an indication of data citations. The Data Usage Metrics group works on a standard for the measurement and display of Data Usage Metrics. Here I explain how publishers and data repositories can contribute to and be…
Mehr
Beschreibung
Research Paper (postgraduate) from the year 2019 in the subject Computer Science - Software, , course: MCA, language: English, abstract: In this paper, I describe the outcomes of the work of the Scholarly Link Exchange (Scholix) working group and the Data Usage Metrics working group. The Scholix working group developed a framework that allows organizations to expose and discover links between articles and datasets, thereby providing an indication of data citations. The Data Usage Metrics group works on a standard for the measurement and display of Data Usage Metrics. Here I explain how publishers and data repositories can contribute to and benefit from these initiatives. Together, these contributions feed into several hubs that enable data repositories to start displaying DLMs. Once these DLMs are available, researchers are in a better position to make their data count and be rewarded for their work. Over the last years, many organizations have been working on infrastructure to facilitate sharing and reuse of research data. This means that researchers now have ways of making their data available, but not necessarily incentives to do so. Several Research Data Alliance (RDA) working groups have been working on ways to start measuring activities around research data to provide input for new Data Level Metrics (DLMs). These DLMs are a critical step towards providing researchers with credit for their work.
CHF 14.50
Preise inkl. MwSt. und Versandkosten (Portofrei ab CHF 40.00)
V103:
Folgt in ca. 5 Arbeitstagen
Produktdetails
- ISBN: 978-3-668-92600-4
- EAN: 9783668926004
- Produktnummer: 31786733
- Verlag: Grin Verlag
- Sprache: Englisch
- Erscheinungsjahr: 2019
- Seitenangabe: 16 S.
- Masse: H21.0 cm x B14.8 cm x D0.1 cm 40 g
- Abbildungen: Booklet
- Gewicht: 40
Über den Autor
20+ Years of strong teaching experience for Under Graduate and Post Graduate courses of Computer Science across several colleges of Patna University and NIT Patna, Bihar, IND. Written several Computer Science academic books ( http://www.amazon.com/author/ajitsingh) and published several research papers across the World. [Memberships]1. InternetSociety (2168607) - Japan/France/Delhi/Trivendrum Chapters2. IEEE (95539159)3. International Association of Engineers (IAENG-233408)4. Eurasia Research STRA-M193715. ORCID https://orcid.org/0000-0002-6093-34576. Python Software Foundation7. Data Science Association8. Non Fiction Authors Association (NFAA-21979)9. IoT Council
66 weitere Werke von Ajit Singh:
Ebook (PDF Format)
CHF 3.00
Bewertungen
0 von 0 Bewertungen
Anmelden
Keine Bewertungen gefunden. Seien Sie der Erste und teilen Sie Ihre Erkenntnisse mit anderen.