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

Abstract

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.

Using ORCID, DOI, and Other Open Identifiers in Research Evaluation

“…An example of the contextual richness that can be achieved using these endpoints, even with a relatively constrained set of information types, is provided by the Research Graph initiative (Aryani et al, 2018) (see Figure 2). Research Graph is an open collaborative effort to connect scholarly records across global research repositories.…”

“…Funders and other agencies collect a significant volume of information about researchers and their contributions at the FIGURE 2 | The research graph meta model (Aryani et al, 2018). point of project applications or proposals.…”

Integrated management of innovation in university-driven open ecosystems : an evolutionary approach

“…Specifically, SNA allows for measuring the features of a network and the position of the actors of an innovation ecosystem (Cronin, 2016). It is a quantitative method that helps us obtain the social structure from the relationships established among social entities such as people, groups and organizations (De Nooy et al, 2018;Aryani et al, 2018;Ávila-Toscano, 2009). SNA can be applied, among other things, to analyse large data sets of patent registrations to examine collaboration in research and development or to analyse citations of academic publications to study scientific collaboration and impact.…”

“…SNA can be applied, among other things, to analyse large data sets of patent registrations to examine collaboration in research and development or to analyse citations of academic publications to study scientific collaboration and impact. For a large number of nodes, it is difficult to manually and systematically visualize and analyse networks, so computer software is normally employed to analyse network data (Aryani et al, 2018;Akhtar, 2014;Studer et al, 1998). Referring to data collection, rational data is collected by observation, questionnaires, surveys or ethnographic methods, and processed through formal procedures based on graph theory and matrix theory.…”

“…Below are some examples founded that could be of interest in this or other subsequent iterations to improve the innovation ecosystem ontology: There are coming up several initiatives to create frameworks and connections with the articles datasets and other sources such as grants, researchers, etc. A Research Graph dataset for connecting research data repositories using RD-Switchboard is proposed in the paper ofAryani et al (2018). Another example is FABIO 100 . The FRBR-aligned Bibliographic Ontology (FaBiO) is an ontology for describing entities that are published or potentially publishable (e.g., journal articles, conference papers, books), and that contain or are referred to by bibliographic references.-Patents  A patent system ontology for facilitating retrieval of patent related information is proposed byTaduri et al…”