The Data-Literature Interlinking Service
Creators
- 1. Australian National Data Service
- 2. Elsevier
- 3. Institute of Information Science and Technology, CNR
- 4. PANGAEA
Description
Research data publishing is today widely regarded as crucial for reproducibility, proper assessment of scientific results, and as a way for researchers to get proper credit for sharing their data. However, several challenges need to be solved to fully realize its potential, one of them being the development of a global standard for links between research data and literature. Current linking solutions are mostly based on bilateral, ad-hoc agreements between publishers and data centers. These operate in silos so that content cannot be readily combined to deliver a network graph connecting research data and literature in a comprehensive and reliable way. The RDA Publishing Data Services Working Group (PDS-WG) aims to address this issue of fragmentation by bringing together different stakeholders to agree on a common infrastructure for sharing links between datasets and literature. This paper presents the synergic effort of the PDS-WG and the OpenAIRE infrastructure to achieve these objectives by realizing and operating the Data-Literature Interlinking Service. The Service populates and provides access to a graph of dataset-literature links (at the time of writing close to five millions, and growing) collected from a variety of major data centers, publishers, and research organizations. To achieve its objectives the Service proposes an interoperable exchange data model and format, based on which it collects and publishes links, thereby offering the opportunity to validate such common approach on real-case scenarios, with real providers and consumers. Feedback of these actors will drive continuous refinement of the both data model and exchange format, supporting the further development of the Service to become an essential part of a universal, open, cross-platform, cross-discipline solution for collecting and sharing dataset-literature links
Notes
Files
2017_386407.preprint.pdf
Files
(1.4 MB)
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