Improving Access to Scientific Literature with Knowledge Graphs

@article{Auer2020ImprovingAT,
  title={Improving Access to Scientific Literature with Knowledge Graphs},
  author={S. Auer and Allard Oelen and Muhammad Haris and Markus Stocker and Jennifer D'Souza and Kheir Eddine Farfar and Lars Vogt and Manuel Prinz and Vitalis Wiens and Mohamad Yaser Jaradeh},
  journal={Bibliothek Forschung und Praxis},
  year={2020},
  volume={44},
  pages={516 - 529}
}
Abstract The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based-formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this article, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage… 
Researcher or Crowd Member? Why not both! The Open Research Knowledge Graph for Applying and Communicating CrowdRE Research
TLDR
A curated qualitative and quantitative scholarly knowledge in the ORKG is curated based on papers contained in two previously published systematic literature reviews on CrowdRE, which improves access and communication of the scholarly knowledge about CrowdRE research.
Overview of STEM Science as Process, Method, Material, and Data Named Entities
TLDR
This study develops and analyzes a large-scale structured dataset of STEM articles across 10 different disciplines, and presents a feasibility test of characterizing multidisciplinary science with domain-independent concepts.
Knowledge Graph Question Answering Leaderboard: A Community Resource to Prevent a Replication Crisis
TLDR
A new central and open leaderboard for any KGQA benchmark dataset as a focal point for the community is provided https://kgqa.github.io/leaderboard/.
SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly NLP Contributions for a Research Knowledge Graph
TLDR
The SemEval-2021 Shared Task NLPContributionGraph tasks participants to develop automated systems that structure contributions from NLP scholarly articles in the English language at three levels of information granularity, i.e. at sentence-level, phrase- level, and phrases organized as triples toward Knowledge Graph (KG) building.
Designing, implementing and deploying an Enterprise Knowledge Graph from A to Z
TLDR
The aim in this tutorial is to familiarize the audience with the complete development and integration of an EKG.
Pattern-based Acquisition of Scientific Entities from Scholarly Article Titles
TLDR
A rule-based approach for the automatic acquisition of salient scientific entities from Computational Linguistics (CL) scholarly article titles by selecting lexico-syntactic patterns that were easily recognizable, occurred frequently, and positionally indicated a scientific entity type.
A Visual SHACL Shapes Editor Based On OntoPad
TLDR
A tool to support a two-step-process to model a terminology and a schema with a combined graphical RDF Schema editor and visual SHACL editor is presented.
A Hybrid Intelligent Approach for the Support of Higher Education Students in Literature Discovery
TLDR
A hybrid intelligent approach that combines knowledge engineering, machine learning, and human intervention to automatically recommend literature resources relevant for a high quality of literature discovery is presented.
A Scholarly Knowledge Graph-Powered Dashboard: Implementation and User Evaluation
TLDR
A dashboard is presented, which visualizes the research contributions on an educational science topic in the frame of the Open Research Knowledge Graph (ORKG), which can be used for the development of scholarly knowledge graph-powered dashboards in different domains.

References

SHOWING 1-10 OF 16 REFERENCES
Creating a Scholarly Knowledge Graph from Survey Article Tables
TLDR
A human-in-the-loop methodology used to build a scholarly knowledge graph leveraging literature survey articles, demonstrating the feasibility of the approach, but also indicating that manual effort is required and thus underscore the important role of human experts.
Question Answering on Scholarly Knowledge Graphs
TLDR
JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs to retrieve direct answers to a variety of different questions asked ontabular data in articles is presented.
Construction of the Literature Graph in Semantic Scholar
TLDR
This paper reduces literature graph construction into familiar NLP tasks, point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task.
Generate FAIR Literature Surveys with Scholarly Knowledge Graphs
TLDR
This work presents a methodology and a system for comparing scholarly literature, in particular research contributions describing the addressed problem, utilized materials, employed methods and yielded results, using a scholarly knowledge graph.
An Overview of Microsoft Academic Service (MAS) and Applications
TLDR
A knowledge driven, highly interactive dialog that seamlessly combines reactive search and proactive suggestion experience, and a proactive heterogeneous entity recommendation are demonstrated.
Domain-Independent Extraction of Scientific Concepts from Research Articles
TLDR
A set of generic scientific concepts that have been identified in a systematic annotation process are suggested and used to annotate a corpus of scientific abstracts from 10 domains of Science, Technology and Medicine at the phrasal level in a joint effort with domain experts.
Unleashing Tabular Content to Open Data: A Survey on PDF Table Extraction Methods and Tools
TLDR
This paper aims at providing a structured and comprehensive overview of the research in tabular content extraction specifically from PDF documents as well as to provide an overview of most recent practical results in the literature.
GROBID: Combining Automatic Bibliographic Data Recognition and Term Extraction for Scholarship Publications
Based on state of the art machine learning techniques, GROBID (GeneRation Of BIbliographic Data) performs reliable bibliographic data extractions from scholar articles combined with multi-level term
Educational research, an introduction
TLDR
A systematic review of research methods and techniques used in qualitative and quantitative education, and some of the approaches taken, found that qualitative research is more effective than quantitative research on a number of fronts.
2020a): Generate FAIR Literature Surveys with Scholarly Knowledge Graphs. In: JCDL ’20
  • Proceedings of the ACM/IEEE Joint Conference on Digital
  • 2020
...
...