Facets, Tiers and Gems: Ontology Patterns for Hypernormalisation

There are many methodologies and techniques for easing the task of ontology building. Here we describe the intersection of two of these: ontology normalisation and fully programmatic ontology development. The first of these describes a standardized organisation for an ontology, with singly inherited self-standing entities, and a number of small taxonomies of refining entities. The former are described and defined in terms of the latter and used to manage the polyhierarchy of the self-standing entities. Fully programmatic development is a technique where an ontology is developed using a domain-specific language within a programming language, meaning that as well defining ontological entities, it is possible to add arbitrary patterns or new syntax within the same environment. We describe how new patterns can be used to enable a new style of ontology development that we call hypernormalisation

Linking with Meaning: Ontological Hypertext for Scholars

The links in ontological hypermedia are defined according to the relationships between real-world objects. An ontology that models the significant objects in a scholar’s world can be used toward producing a consistently interlinked research literature. Currently the papers that are available online are mainly divided between subject- and publisher-specific archives, with little or no interoperability. This paper addresses the issue of ontological interlinking, presenting two experimental systems whose hypertext links embody ontologies based on the activities of researchers and scholars

Untangling the Web of E-Research: Towards a Sociology of Online Knowledge

e-Research is a rapidly growing research area, both in terms of publications and in terms of funding. In this article we argue that it is necessary to reconceptualize the ways in which we seek to measure and understand e-Research by developing a sociology of knowledge based on our understanding of how science has been transformed historically and shifted into online forms. Next, we report data which allows the examination of e-Research through a variety of traces in order to begin to understand how the knowledge in the realm of e-Research has been and is being constructed. These data indicate that e-Research has had a variable impact in different fields of research. We argue that only an overall account of the scale and scope of e-Research within and between different fields makes it possible to identify the organizational coherence and diffuseness of e-Research in terms of its socio-technical networks, and thus to identify the contributions of e-Research to various research fronts in the online production of knowledge

Ontology Design Patterns for bio-ontologies: a case study on the Cell Cycle Ontology

<p>Abstract</p> <p>Background</p> <p>Bio-ontologies are key elements of knowledge management in bioinformatics. Rich and rigorous bio-ontologies should represent biological knowledge with high fidelity and robustness. The richness in bio-ontologies is a prior condition for diverse and efficient reasoning, and hence querying and hypothesis validation. Rigour allows a more consistent maintenance. Modelling such bio-ontologies is, however, a difficult task for bio-ontologists, because the necessary richness and rigour is difficult to achieve without extensive training.</p> <p>Results</p> <p>Analogous to design patterns in software engineering, Ontology Design Patterns are solutions to typical modelling problems that bio-ontologists can use when building bio-ontologies. They offer a means of creating rich and rigorous bio-ontologies with reduced effort. The concept of Ontology Design Patterns is described and documentation and application methodologies for Ontology Design Patterns are presented. Some real-world use cases of Ontology Design Patterns are provided and tested in the Cell Cycle Ontology. Ontology Design Patterns, including those tested in the Cell Cycle Ontology, can be explored in the Ontology Design Patterns public catalogue that has been created based on the documentation system presented (<url>http://odps.sourceforge.net/</url>).</p> <p>Conclusions</p> <p>Ontology Design Patterns provide a method for rich and rigorous modelling in bio-ontologies. They also offer advantages at different development levels (such as design, implementation and communication) enabling, if used, a more modular, well-founded and richer representation of the biological knowledge. This representation will produce a more efficient knowledge management in the long term.</p

BAMS Neuroanatomical Ontology: Design and Implementation

We describe in this paper the structure and main features of a domain specific ontology for neuroscience, the BAMS Neuroanatomical Ontology. The ontology includes a complete set of concepts that describe the parts of the rat nervous system, a growing set of concepts that describe neuron populations identified in different brain regions, and relationships between concepts. The ontology is linked with a complex representation of structural and physiological variables used to classify neurons, which is encoded in BAMS. BAMS Neuroanatomical Ontology is accessible on the web and includes an interface that allows browsing terms, viewing criteria for classification, and accessing associated information

A true competitive advantage? Reflections on different epistemological approaches to strategy research

In this paper, the authors focus on the theory of truth underlying specific traditions in strategy research. They distinguish positivism, constructionism, scientific realism, and pragmatism as viable, but fundamentally different epistemological approaches. The authors argue that each of these approaches is based on a specific theory of truth.truth; strategy; competitive advantage

Toward an Interoperability and Integration Framework to Enable Digital Thread

This article discusses ongoing research investigating the feasibility of supporting an interoperability and integration framework to enable the digital thread, or an authoritative source of truth with current technology. The question that initiated this exploratory research was, “Is there current technology that can enable cross-domain digital artifact data sharing needed for the digital thread?” A thorough review and investigation of current state-of-the-art model-based systems engineering was performed by reviewing literature and performing multiple site visits and interviews with organizations at the forefront of digital engineering. After this initial investigation and review, a Semantic Web-enabled framework that would allow data in the thread to be captured, stored, transferred, checked for completeness and consistency, and changed under revision change control management began to be formed. This framework has gone through revisions. This paper reflects the most current demonstration of the framework and its capability of acquiring digital data, and parsing and querying the data using Semantic Web technology to generate a decision table that allows the decision data to be visualized. The article concludes with future demonstrations of the framework to further advance toward a framework that can enable a digital thread in practice

Knowledge Author: Facilitating user-driven, Domain content development to support clinical information extraction

Background: Clinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts, their lexical variants, and associated modifiers to accurately extract information from clinical texts. An NLP system leverages this schema to structure concepts and extract meaning from the free texts. In the clinical domain, creating a semantic schema typically requires input from both a domain expert, such as a clinician, and an NLP expert who will represent clinical concepts created from the clinician's domain expertise into a computable format usable by an NLP system. The goal of this work is to develop a web-based tool, Knowledge Author, that bridges the gap between the clinical domain expert and the NLP system development by facilitating the development of domain content represented in a semantic schema for extracting information from clinical free-text. Results: Knowledge Author is a web-based, recommendation system that supports users in developing domain content necessary for clinical NLP applications. Knowledge Author's schematic model leverages a set of semantic types derived from the Secondary Use Clinical Element Models and the Common Type System to allow the user to quickly create and modify domain-related concepts. Features such as collaborative development and providing domain content suggestions through the mapping of concepts to the Unified Medical Language System Metathesaurus database further supports the domain content creation process. Two proof of concept studies were performed to evaluate the system's performance. The first study evaluated Knowledge Author's flexibility to create a broad range of concepts. A dataset of 115 concepts was created of which 87 (76%) were able to be created using Knowledge Author. The second study evaluated the effectiveness of Knowledge Author's output in an NLP system by extracting concepts and associated modifiers representing a clinical element, carotid stenosis, from 34 clinical free-text radiology reports using Knowledge Author and an NLP system, pyConText. Knowledge Author's domain content produced high recall for concepts (targeted findings: 86%) and varied recall for modifiers (certainty: 91% sidedness: 80%, neurovascular anatomy: 46%). Conclusion: Knowledge Author can support clinical domain content development for information extraction by supporting semantic schema creation by domain experts