Institute of Artificial Intelligence LUHAI Institute News
Invited Talk by Dr. Jennifer D'Souza on April 20th

Invited Talk by Dr. Jennifer D'Souza on April 20th

The LUH|AI invites you to an upcoming invited talk:

Speaker

Dr. Jennifer D'Souza

Leibniz Information Centre for Science and Technology University Library

https://www.tib.eu/en/research-development/research-groups-and-labs/data-science-digital-libraries/staff/jennifer-dsouza

 

Time and location

April 20, 16:00, 3408-1630 (Appelstr. 9A)

 

Title

Semantic Publishing of Scientific Contributions in the Open Research Knowledge Graph

 

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 talk, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.


External participants (i.e. neither students nor employees of LUH) are kindly requested to send a short, informal email to office@ai.uni-hannover.de to register.