Definitions in ontologies

Definitions vary according to context of use and target audience. They must be made relevant for each context to fulfill their cognitive and linguistic goals. This involves adapting their logical structure, type of content, and form to each context of use. We examine from these perspectives the case of definitions in ontologies

An Introduction to Ontology

Analytical philosophy of the last one hundred years has been heavily influenced by a doctrine to the effect that one can arrive at a correct ontology by paying attention to certain superficial (syntactic) features of first-order predicate logic as conceived by Frege and Russell. More specifically, it is a doctrine to the effect that the key to the ontological structure of reality is captured syntactically in the ‘Fa’ (or, in more sophisticated versions, in the ‘Rab’) of first-order logic, where ‘F’ stands for what is general in reality and ‘a’ for what is individual. Hence “f(a)ntology”. Because predicate logic has exactly two syntactically different kinds of referring expressions—‘F’, ‘G’, ‘R’, etc., and ‘a’, ‘b’, ‘c’, etc.—so reality must consist of exactly two correspondingly different kinds of entity: the general (properties, concepts) and the particular (things, objects), the relation between these two kinds of entity being revealed in the predicate-argument structure of atomic formulas in first-order logic

A machine learning pipeline for discriminant pathways identification

Motivation: Identifying the molecular pathways more prone to disruption during a pathological process is a key task in network medicine and, more in general, in systems biology. Results: In this work we propose a pipeline that couples a machine learning solution for molecular profiling with a recent network comparison method. The pipeline can identify changes occurring between specific sub-modules of networks built in a case-control biomarker study, discriminating key groups of genes whose interactions are modified by an underlying condition. The proposal is independent from the classification algorithm used. Three applications on genomewide data are presented regarding children susceptibility to air pollution and two neurodegenerative diseases: Parkinson's and Alzheimer's. Availability: Details about the software used for the experiments discussed in this paper are provided in the Appendix

Improving model quality through foundational ontologies: Two contrasting approaches to the representation of roles

Several foundational ontologies have been developed recently. We examine two of these from the point of view of their quality in representing temporal changes, focusing on the example of roles. We discuss how these are modelled in two foundational ontologies: the Unified Foundational Ontology and the BORO foundational ontology. These exhibit two different approaches, endurantist and perdurantist respectively. We illustrate the differences using a running example in the university student domain, wherein one individual is not only a registered student but also, for part of this period, was elected the President of the Student Union. The metaphysical choices made by UFO and BORO lead to different representations of roles. Two key differences which affect the way roles are modelled are exemplified in this paper: (1) different criteria of identity and (2) differences in the way individual objects extend over time and possible worlds. These differences impact upon the quality of the models produced in terms of their respective explanatory power. The UFO model concentrates on the notion of validity in “all possible worlds” and is unable to accurately represent the way particulars are extended in time. The perdurantist approach is best able to describe temporal changes wherein roles are spatio-temporal extents of individuals

An improved ontological representation of dendritic cells as a paradigm for all cell types

<p>Abstract</p> <p>Background</p> <p>Recent increases in the volume and diversity of life science data and information and an increasing emphasis on data sharing and interoperability have resulted in the creation of a large number of biological ontologies, including the Cell Ontology (CL), designed to provide a standardized representation of cell types for data annotation. Ontologies have been shown to have significant benefits for computational analyses of large data sets and for automated reasoning applications, leading to organized attempts to improve the structure and formal rigor of ontologies to better support computation. Currently, the CL employs multiple <it>is_a </it>relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL's utility for computation and for cross-species data integration.</p> <p>Results</p> <p>To enhance the CL's utility for computational analyses, we developed a method for the ontological representation of cells and applied this method to develop a dendritic cell ontology (DC-CL). DC-CL subtypes are delineated on the basis of surface protein expression, systematically including both species-general and species-specific types and optimizing DC-CL for the analysis of flow cytometry data. We avoid multiple uses of <it>is_a </it>by linking DC-CL terms to terms in other ontologies via additional, formally defined relations such as <it>has_function</it>.</p> <p>Conclusion</p> <p>This approach brings benefits in the form of increased accuracy, support for reasoning, and interoperability with other ontology resources. Accordingly, we propose our method as a general strategy for the ontological representation of cells. DC-CL is available from <url>http://www.obofoundry.org</url>.</p

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution

<p>Abstract</p> <p>Background</p> <p>Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data.</p> <p>Results</p> <p>We present GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution. GOMMA utilizes a generic repository to uniformly and efficiently manage ontology versions and different kinds of mappings. Furthermore, it provides components for ontology matching, and determining evolutionary ontology changes. These components are used by analysis tools, such as the Ontology Evolution Explorer (OnEX) and the detection of unstable ontology regions. We introduce the component-based infrastructure and show analysis results for selected components and life science applications. GOMMA is available at <url>http://dbs.uni-leipzig.de/GOMMA</url>.</p> <p>Conclusions</p> <p>GOMMA provides a comprehensive and scalable infrastructure to manage large life science ontologies and analyze their evolution. Key functions include a generic storage of ontology versions and mappings, support for ontology matching and determining ontology changes. The supported features for analyzing ontology changes are helpful to assess their impact on ontology-dependent applications such as for term enrichment. GOMMA complements OnEX by providing functionalities to manage various versions of mappings between two ontologies and allows combining different match approaches.</p

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Improving Schema Mapping by Exploiting Domain Knowledge

This dissertation addresses the problem of semi-automatically creating schema mappings. The need for developing schema mappings is a pervasive problem in many integration scenarios. Although the problem is well-known and a large body of work exists in the area, the development of schema mappings is today largely performed manually in industrial integration scenarios. In this thesis an approach for the semi-automatic creation of high quality schema mappings is developed

BAICE Thematic Forum:Challenging deficit discourses in international education and development

Research and policy in international education has o en been framed in terms of a deficit discourse. For instance, policy debates on women’s literacy and education have begun by positioning women as a group who need to ‘catch up’ on certain skills in order to become more active in development. Rather than recognising the skills and knowledge that participants already have and prac se in their everyday lives, researchers who adopt this deficit perspective on learning and education may find that the research agenda and questions will already be shaped to a large extent by the providers’/ policy makers’ standpoint. This BAICE Thematic Forum aimed to deepen understanding around how deficit discourses have shaped the questions and objectives of international educational research. As well as deconstructing and gaining greater knowledge into why and how these dominant deficit discourses have influenced the research agenda, we also set out to investigate and propose alternative conceptual models through two linked seminars. The seminars were intended to explore and challenge dominant deficit discourses that have shaped the way researchers/policy makers look at specific groups in development and thematic policy areas