Yuanxi Fu: Representing and reusing scientific evidence

Title: Representing and reusing scientific evidence
Session Lead: Yuanxi Fu
Time: 11 am – noon, Wednesday, 2021-03-17
Location: Zoom
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Historically, scientific evidence that supports or counters a hypothesis is locked in the form of research papers. Such text-bound existence increases the difficulty of reusing evidence at a later time. Users must read through a research paper and extract relevant information manually. Moreover, the task of comparison and synthesis is time-consuming and demands a high level of domain expertise. In my opinion, reuse and representation are interrelated issues. In this discussion session, I will first use a network visualization study of a public health controversy to illustrate the challenge of reusing scientific evidence (Hsiao et al., 2020). Then I will introduce four different ontologies that are capable of representing scientific evidence: The micropublication ontology (Clark et al.,2014), the Scientific Evidence and Provenance Information Ontology (SEPIO) (Brush et al., 2016), the Reasoning and Discourse Ontology (RDO) (Bölling et al., 2013), and the Evidence Ontology (ECO) (Chibucos et al., 2014). Those ontologies also enable argument-based modeling of scientific papers, a foundation for the Keystone Framework (Fu & Schneider, 2020), which tracks validity dependencies among scientific papers. My future work will focus on automated extraction of methods keystone citations and constructing knowledge graph of methods (Fu et al., 2021). I expect a good discussion around the representation of scientific evidence, with a focus on how to make the reuse easier.