The Scholix Framework for Interoperability in Data-Literature Information Exchange

Burton, Adrian; Aryani, Amir; Koers, Hylke; Manghi, Paolo; Bruzzo, Sandro La; Stocker, Markus; Diepenbroek, Michael; Schindler, Uwe; Fenner, Martin

doi:10.1045/january2017-burton

Cited by 54 publications

(40 citation statements)

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“…Multiple efforts try to address this. One effort directly related to scholarly publishing is the Scholix (Scholarly Link Exchange) initiative which emerged out of RDA to more formally interconnect data and literature (Burton et al 2017). The approach is functional and operational, as it builds from established citation hubs like DataCite, CrossRef, and OpenAire.…”

Section: Tracking Use and Impactmentioning

confidence: 99%

The History and Future of Data Citation in Practice

Parsons

Duerr

Jones

2019

Data Science Journal

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In this review, we adopt the definition that 'Data citation is a reference to data for the purpose of credit attribution and facilitation of access to the data' (TGDCSP 2013: CIDCR6). Furthermore, access should be enabled for both humans and machines (DCSG 2014). We use this to discuss how data citation has evolved over the last couple of decades and to highlight issues that need more research and attention. Data citation is not a new concept, but it has changed and evolved considerably since the beginning of the digital age. Basic practice is now established and slowly but increasingly being implemented. Nonetheless, critical issues remain. These issues are primarily because we try to address multiple human and computational concerns with a system originally designed in a non-digital world for more limited use cases. The community is beginning to challenge past assumptions, separate the multiple concerns (credit, access, reference, provenance, impact, etc.), and apply different approaches for different use cases.

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Section: Tracking Use and Impactmentioning

confidence: 99%

The History and Future of Data Citation in Practice

Parsons

Duerr

Jones

2019

Data Science Journal

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“…Researchers are now gaining access to a broader range of data repositories, including university data storage, discipline-specific repositories, and national (regional) level data infrastructures. The main issue is that these infrastructures often operate in silos so that their research data collections are not connected to other repositories or related research output stored in other platforms 2 .…”

Section: Background and Summarymentioning

confidence: 99%

A Research Graph dataset for connecting research data repositories using RD-Switchboard

et al. 2018

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This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures. The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants. The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation. Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

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“…An additional challenge in characterizing relationships is that different uses of relationship information might require different levels of description about the entities at either end of the relationships. The Scholix framework, for example, defines a very simple data model for representing relationships (Burton, et al, 2017b). For other applications, including our EarthCollab project, a simplistic data model did not support the goals of data discovery and understanding.…”

Section: Requirements For Scholarly Resource Linkingmentioning

confidence: 99%

Scholarly resource linking: Building out a “relationship life cycle”

Mayernik

2018

Proc. Assoc. Info. Sci. Tech.

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Scholarly resources, including publications, software, data sets, and instruments, are created in an iterative and interrelated fashion. Managing the relationships that exist among and between such resources is a central requirement for information systems. Practically, however, many scholarly resources exist online as discrete entities, divorced from other resources to which they are intimately related. A robust system for linking scholarly resources in a broad and sustainable fashion will have to navigate a set of complex and interrelated requirements. This paper presents results and insights from three different projects that focused on supporting more robust linkages among scholarly resources. The discussion details key technical and institutional challenges looking forward and backward in time across what might be considered to be a “relationship life cycle”: identifying, validating, characterizing, and preserving relationships. The goal of the paper is to help guide new research initiatives and operational services focused on integrating relationship information into the scholarly record.

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The Scholix Framework for Interoperability in Data-Literature Information Exchange

Cited by 54 publications

References 0 publications

The History and Future of Data Citation in Practice

The History and Future of Data Citation in Practice

A Research Graph dataset for connecting research data repositories using RD-Switchboard

Scholarly resource linking: Building out a “relationship life cycle”

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