TY - GEN
T1 - Fostering Scientific Meta-analyses with Knowledge Graphs
T2 - 17th Extended Semantic Web Conference, ESWC 2020
AU - Tiddi, Ilaria
AU - Balliet, Daniel
AU - ten Teije, Annette
PY - 2020
Y1 - 2020
N2 - A meta-analysis is a Science of Science method widely used in the medical and social sciences to review, aggregate and quantitatively synthesise a body of studies that address the same research question. With the volume of research growing exponentially every year, conducting meta-analyses can be costly and inefficient, as a significant amount of time and human efforts needs to be spent in finding studies meeting research criteria, annotating them, and properly performing the statistical analyses to summarise the findings. In this work, we show these issues can be tackled with semantic representations and technologies, using a social science scenario as case-study. We show how the domain-specific content of research outputs can be represented and used to facilitate their search, analysis and synthesis. We present the very first representation of the domain of human cooperation, and the application we built on top of this to help experts in performing meta-analyses semi-automatically. Using few application scenarios, we show how our approach supports the various phases meta-analyses, and more in general contributes towards research replication and automated hypotheses generation.
AB - A meta-analysis is a Science of Science method widely used in the medical and social sciences to review, aggregate and quantitatively synthesise a body of studies that address the same research question. With the volume of research growing exponentially every year, conducting meta-analyses can be costly and inefficient, as a significant amount of time and human efforts needs to be spent in finding studies meeting research criteria, annotating them, and properly performing the statistical analyses to summarise the findings. In this work, we show these issues can be tackled with semantic representations and technologies, using a social science scenario as case-study. We show how the domain-specific content of research outputs can be represented and used to facilitate their search, analysis and synthesis. We present the very first representation of the domain of human cooperation, and the application we built on top of this to help experts in performing meta-analyses semi-automatically. Using few application scenarios, we show how our approach supports the various phases meta-analyses, and more in general contributes towards research replication and automated hypotheses generation.
KW - e-Science
KW - Knowledge graphs
KW - Meta-analysis
KW - Science of Science
UR - http://www.scopus.com/inward/record.url?scp=85086144534&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086144534&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-49461-2_17
DO - 10.1007/978-3-030-49461-2_17
M3 - Conference contribution
AN - SCOPUS:85086144534
SN - 9783030494605
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 287
EP - 303
BT - The Semantic Web
A2 - Harth, Andreas
A2 - Kirrane, Sabrina
A2 - Ngonga Ngomo, Axel-Cyrille
A2 - Paulheim, Heiko
A2 - Rula, Anisa
A2 - Gentile, Anna Lisa
A2 - Haase, Peter
A2 - Cochez, Michael
PB - Springer
Y2 - 31 May 2020 through 4 June 2020
ER -
