09:00 - 09:30          Opening

09:30- 10:25 Keynote Speech

Prof. Dr. Maria Esther Vidal (Head of the Scientific Data Management research group)

Prof. Dr. Maria-Esther Vidal is head of the Scientific Data Management research group at the TIB and a member of the L3S research centerat the Leibniz University of Hanover. She is also a full professor (on leave) at the Universidad Simón Bolívar (USB) Venezuela. Her research interests include data and knowledge management, knowledge representation and the semantic web. She has published more than 170 papers on the Semantic Web, databases, bioinformatics and artificial intelligence. She is co-author of a monograph and co-editor of books and magazine specials. Vidal is a member of various editorial boards (e.g. JWS, JDIQ) and has been director general, co-chair, senior member and reviewer of several scientific events and journals (e.g. ESWC, AAAI, AMW, WWW, KDE). She leads data management in the EU H2020 projects iASiS, BigMedylitics and QualiChain and has contributed to BigDataEurope, BigDataOcean and the MSCA ETN projects WDAqua and NoBIAS. She was a visiting professor at various universities (e.g. Uni Maryland, UPM Madrid, UPC, KIT Karlsruhe, Uni Nantes). In the past she has participated in international projects (e.g. FP7, NSF, AECI) and led industrial data integration projects (e.g. Bell South, Telefonica) for more than ten years.

Keynote: Can Knowledge Graphs Contribute to Personalized Therapies?

Data silos dominate the health sector, and relevant patient data is scattered across heterogeneous data sources and fragmented biomedical vocabularies. The data silos, more often than not, prevent a combination, analysis, and re-use of these data and thus forestall the evolution of invaluable insights for decision-making in healthcare. 

This talk will position knowledge-driven ecosystems as powerful frameworks for integrating health data silos into knowledge graphs. Ontologies describe the meaning of the combined data, and mapping rules enable the declarative definition of the transformation and integration processes. 

We will show the benefits of exploiting knowledge graphs and symbolic learning to uncover patterns contributing to a better understanding of lung cancer. Additionally, we will present neuro-symbolic systems on top of knowledge graphs implemented to predict the effectiveness of cancer treatment and the effects of drug-drug interactions. Lastly, we will discuss the lessons learned in developing the knowledge-driven ecosystems in the context of the EU H2020 project CLARIFY and their role in individualized decision-making.

10:30 – 11:00 Coffee Break

11:00 - 12:30

Session 1: Machine Learning and Artificial Intelligence on Healthcare and Life Sciences Data

• On the Potential of Artificial Intelligence Chatbots for Data Exploration of Federated Bioinformatics Knowledge Graphs. Ana Claudia Sima and Tarcisio M. Farias

• Towards Machine-Assisted Biomedical Data Preparation: A Use Case on Disparity in Access to Health Care. Paulo Pinheiro, Henrique Santos, Miao Qi, Kristin P. Bennett and Deborah L. McGuinness

12:30 – 14:00 Lunch Break

14:00 - 14:45    Keynote Speech: Professor Stefan Decker

Stefan Decker is a computer scientist, Full Professor for Database and Information Systems at RWTH Aachen University, and managing director of the Fraunhofer Institute for Applied Information Technology. He specializes in the Semantic Web. As of 25 January 2020, his research reached 21,206 (with h-index of 66 and i10-index of 201) Google Scholar Citations, making him one of the most influential Semantic Web researchers.

He was formerly Professor of Digital Enterprise at the National University of Ireland Galway, and executive director of the Digital Enterprise Research Institute, Galway. Prof. Decker studied Computer Science at the University of Kaiserslautern. He received his doctorate at the Karlsruhe Technical University. He was elected to the Royal Irish Academy in 2010

Keynote: FAIR Dataspace in Healthcare and other Domains

14:45 - 15:30 Session 2: Healthcare and Life Sciences Knowledge Graphs

• Translating Clinical Decision Logic Within Knowledge Graphs to Smart Contracts. William Van Woensel, Manan Shukla and Oshani Seneviratne

15:30 – 16:00 Coffee Break

16:00 - 17:20 Session 3: Data Interoperability in Healthcare and Life Sciences Data and Documents

• Benchmark datasets for biomedical knowledge graphs with negative statements. Rita T. Sousa, Sara Silva and Catia Pesquita

• OntoClue, a framework to compare vector-based approaches for document similarity. Rohitha Ravinder, Tim Fellerhoff, Vishnu Dadi, Lukas Geist, Guillermo Rocamora, Muhammad Talha, Dietrich Rebholz-Schuhmann and Leyla Jael Castro

17:20- 17:30 Closing