The Value of Value Sets

A common definition of value set will be provided and fully characterized relative to its proposed uses. We will describe, compare, and contrast several approaches to specifying and referencing value sets in a stable manner over time. The term “value set”, although ubiquitous within biomedical informatics has no common definition and has yet to be fully described in a formal manner. It is essential for the design and launch of new ontologies, biomedical informatics applications and data sharing environments that a common and well-­‐ understood definition of “value set” is provided. It is also essential that options and trade-­‐offs be understood for what type of technology is appropriate for the implementation and usage of particular types of value set for particular use cases

LexOWL: A Bridge from LexGrid to OWL

The Lexical Grid project is an on-going community driven initiative that provides a common terminology model to represent multiple vocabulary and ontology sources as well as a scalable and robust API for accessing such information. In order to add more powerful functionalities to the existing infrastructure and align LexGrid more closely with various Semantic Web technologies, we introduce the LexOWL project for representing the ontologies modeled within the LexGrid environment in OWL (Web Ontology Language). The crux of this effort is to create a “bridge” that functionally connects the LexBIG (a LexGrid API) and the OWL API (an interface that implements OWL) seamlessly. In this paper, we discuss the key aspects of designing and implementing the LexOWL bridge. We compared LexOWL with other OWL converting tools and conclude that LexOWL provides an OWL mapping and converting tool with well-defined interoperability for information in the biomedical domain

LexOWL: A Bridge from LexGrid to OWL

The Lexical Grid project is an on-going community driven initiative that provides a common terminology model to represent multiple vocabulary and ontology sources as well as a scalable and robust API for accessing such information. In order to add more powerful functionalities to the existing infrastructure and align LexGrid more closely with various Semantic Web technologies, we introduce the LexOWL project for representing the ontologies modeled within the LexGrid environment in OWL (Web Ontology Language). The crux of this effort is to create a “bridge” that functionally connects the LexBIG (a LexGrid API) and the OWL API (an interface that implements OWL) seamlessly. In this paper, we discuss the key aspects of designing and implementing the LexOWL bridge. We compared LexOWL with other OWL converting tools and conclude that LexOWL provides an OWL mapping and converting tool with well-defined interoperability for information in the biomedical domain

National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease

Complexity and Expressiveness of ShEx for RDF

International audienceWe study the expressiveness and complexity of Shape Expression Schema (ShEx), a novel schema formalism for RDF currently under development by W3C. ShEx assigns types to the nodes of an RDF graph and allows to constrain the admissible neighborhoods of nodes of a given type with regular bag expressions (RBEs). We formalize and investigate two alternative semantics, multi-and single-type, depending on whether or not a node may have more than one type. We study the expressive power of ShEx and study the complexity of the validation problem. We show that the single-type semantics is strictly more expressive than the multi-type semantics, single-type validation is generally intractable and multi-type validation is feasible for a small (yet practical) subclass of RBEs. To curb the high computational complexity of validation, we propose a natural notion of determinism and show that multi-type validation for the class of deterministic schemas using single-occurrence regular bag expressions (SORBEs) is tractable