An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.

One of the long-standing challenges in natural language processing is uniquely identifying entities in text, which when performed accurately and with formal ontologies, supports efforts such as semantic search and question-answering.

Interest in polymer nanocomposites has been increasing because of their unique properties. Since the field draws on a wide range of disciplines, a data resource aimed at adequately supporting the field needs to include vocabulary from many disciplines.

Ontologies are being widely used across many scientific fields, most notably in roles related to acquiring, preparing, integrating and managing data resources.

We address the problem of characterizing breast cancer, which today is done using staging guidelines. Our demo will show different breast cancer staging results that leverage the Whyis semantic nanopublication knowledge graph framework [8].

To investigate the cause and progression of a phenomenon, such as chronic disease, it is essential to collect a wide variety of data that together explains the complex interplay of different factors, e.g., genetic, lifestyle, environmental and social.

We address the problem of modeling study populations in research studies in a declarative manner. Research studies often have a great degree of variability in the reporting of population descriptions.

With the hype around blockchain technologies, misinformation on ‘get rich quick’ scams are becoming rampant. In this work, we describe a solution that puts in the groundwork to identify fraudulent users and track them across multiple blockchains using semantic modeling.

We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo).

A retrospective analysis of administrative claims data from a large U.S. health insurer was performed to study a potential association between oral antibiotic use during early childhood and occurrence of later gastrointestinal (GI) symptoms in children with autism spectrum disorder (ASD).