DLIRMay 20, 2020

Requirements Analysis for an Open Research Knowledge Graph

arXiv:2005.10334v111 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the issue of fragmented and inefficient science communication for researchers, but it is incremental as it builds on existing KG proposals by broadening the scope.

The paper tackles the problem of science communication bottlenecks by analyzing requirements for an Open Research Knowledge Graph (ORKG) to organize scientific information, resulting in a mapping of necessary and desirable requirements and outlining solutions.

Current science communication has a number of drawbacks and bottlenecks which have been subject of discussion lately: Among others, the rising number of published articles makes it nearly impossible to get an overview of the state of the art in a certain field, or reproducibility is hampered by fixed-length, document-based publications which normally cannot cover all details of a research work. Recently, several initiatives have proposed knowledge graphs (KGs) for organising scientific information as a solution to many of the current issues. The focus of these proposals is, however, usually restricted to very specific use cases. In this paper, we aim to transcend this limited perspective by presenting a comprehensive analysis of requirements for an Open Research Knowledge Graph (ORKG) by (a) collecting daily core tasks of a scientist, (b) establishing their consequential requirements for a KG-based system, (c) identifying overlaps and specificities, and their coverage in current solutions. As a result, we map necessary and desirable requirements for successful KG-based science communication, derive implications and outline possible solutions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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