Towards a Knowledge Graph for Science

Towards a Knowledge Graph for Science
Towards a Knowledge Graph for Science
Bibliographical Metadata
Subject:	Scholarly communication
Keywords:	Knowledge Graph, Science and Technology, Research Infrastructure, Libraries, Information Science
Year:	2018
Authors:	Sören Auer, Viktor Kovtun, Manuel Prinz, Anna Kasprzik, Markus Stocker
Venue	WIMS
Content Metadata
Problem:	Semantifying scholarly artifacts
Approach:	Creating a knowledge graph for science
Implementation:	-
Evaluation:	-

Abstract

The document-centric workflows in science have reached (or already exceeded) the limits of adequacy. This is emphasized by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. This presents an opportunity to rethink the dominant paradigm of document-centric scholarly information communication and transform it into knowledge-based information flows by representing and expressing information through semantically rich, interlinked knowledge graphs. At the core of knowledge-based information flows is the creation and evolution of information models that establish a common understanding of information communicated between stakeholders as well as the integration of these technologies into the infrastructure and processes of search and information exchange in the research library of the future. By integrating these models into existing and new research infrastructure services, the information structures that are currently still implicit and deeply hidden in documents can be made explicit and directly usable. This has the potential to revolutionize scientific work as information and research results can be seamlessly interlinked with each other and better matched to complex information needs. Furthermore, research results become directly comparable and easier to reuse. As our main contribution, we propose the vision of a knowledge graph for science, present a possible infrastructure for such a knowledge graph as well as our early attempts towards an implementation of the infrastructure.

Conclusion

The transition from purely document-centric to a more knowledge-based view on scholarly communication is in line with the current digital transformation of information flows in general and is thus inevitable. However, this also creates a need for the implementation of corresponding tools and workflows supporting the switch. As of now, there are still very few of those tools, and their design and concrete features remain a challenge that is yet to be tackled – collaboratively and in a coordinated manner.

Future work

The work presented here delineates our initial steps towards a knowledge graph for science. By testing existing and developing new components, we have so far focused on some core technical aspects of the infrastructure. Naturally, there are a number of research problems and implementation issues as well as a range of socio-technical aspects that need to be addressed in order to realize the vision. Dimensions of open challenges are, among others: • the low-threshold integration of researchers through methods of crowd-sourcing, human-machine interaction, and social networks; • automated analysis, quality assessment, and completion of the knowledge graph as well as interlinking with external sources; • support for representing fuzzy information, scientific discourse and the evolution of knowledge; • development of new methods of exploration, retrieval, and visualization of knowledge graph information.

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Evaluation

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