This introduction presents the main motivations for the development of Description Logics (DLs) as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition. In addition, we provide the reader with an overview of the entire book and some guidelines for reading it. We first address the relationship between Description Logics and earlier semantic network and frame systems, which represent the original heritage of the field. We delve into some of the key problems encountered with the older efforts. Subsequently, we introduce the basic features of DL languages and related reasoning techniques. DL languages are then viewed as the core of knowledge representation systems, considering both the structure of a DL knowledge base and its associated reasoning services. The development of some implemented knowledge representation systems based on Description Logics and the first applications built with such systems are then reviewed. Finally, we address the relationship of Description Logics to other fields of Computer Science.We also discuss some extensions of the basic representation language machinery; these include features proposed for incorporation in the formalism that originally arose in implemented systems, and features proposed to cope with the needs of certain application domains.

https://assets.cambridge.org/97805218/76254/frontmatter/9780521876254_frontmatter.pdf

The Description Logic Handbook

Motivation:In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses.

Results: The Taverna project has developed a tool for the composition and enactment of bioinformatics workflows for the life sciences community. The tool includes a workbench application which provides a graphical user interface for the composition of workflows. These workflows are written in a new language called the simple conceptual unified flow language (Scufl), where by each step within a workflow represents one atomic task. Two examples are used to illustrate the ease by which in silico experiments can be represented as Scufl workflows using the workbench application.

Availability: The Taverna workflow system is available as open source and can be downloaded with example Scufl workflows from http://taverna.sourceforge.net

/pdf/taverna-a-tool-for-the-composition-and-enactment-of-57hwxmmse3.pdf

Taverna: a tool for the composition and enactment of bioinformatics workflows

The Grid 2: Blueprint for a New Computing Infrastructure

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

/pdf/relations-in-biomedical-ontologies-remdv7m8fw.pdf

Relations in biomedical ontologies

Taverna is an application that eases the use and integration of the growing number of molecular biology tools and databases available on the web, especially web services. It allows bioinformaticians to construct workflows or pipelines of services to perform a range of different analyses, such as sequence analysis and genome annotation. These high-level workflows can integrate many different resources into a single analysis. Taverna is available freely under the terms of the GNU Lesser General Public License (LGPL) from http://taverna.sourceforge.net/.

Taverna: a tool for building and running workflows of services

Life sciences research is based on individuals, often with diverse skills, assembled into research groups. These groups use their specialist expertise to address scientific problems. The in silico experiments undertaken by these research groups can be represented as workflows involving the co-ordinated use of analysis programs and information repositories that may be globally distributed. With regards to Grid computing, the requirements relate to the sharing of analysis and information resources rather than sharing computational power. The myGrid project has developed the Taverna Workbench for the composition and execution of workflows for the life sciences community. This experience paper describes lessons learnt during the development of Taverna. A common theme is the importance of understanding how workflows fit into the scientists' experimental context. The lessons reflect an evolving understanding of life scientists' requirements on a workflow environment, which is relevant to other areas of data intensive and exploratory science.

/pdf/taverna-lessons-in-creating-a-workflow-environment-for-the-122gxlgn7o.pdf

Taverna: lessons in creating a workflow environment for the life sciences

Understanding the logical meaning of any description logic or similar formalism is difficult for most people, and OWL-DL is no exception. This paper presents the most common difficulties encountered by newcomers to the language, that have been observed during the course of more than a dozen workshops, tutorials and modules about OWL-DL and it’s predecessor languages. It emphasises understanding the exact meaning of OWL expressions – proving that understanding by paraphrasing them in pedantic but explicit language. It addresses, specifically, the confusion which OWL’s open world assumption presents to users accustomed to closed world systems such as databases, logic programming and frame languages. Our experience has had a major influence in formulating the requirements for a new set of user interfaces for OWL the first of which are now available as prototypes. A summary of the guidelines and paraphrases and examples of the new interface are provided. The example ontologies are available online.

/pdf/owl-pizzas-practical-experience-of-teaching-owl-dl-common-3rq20hlnij.pdf

OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns

The growing quantity and distribution of bioinformatics resources means that finding and utilizing them requires a great deal of expert knowledge, especially as many resources need to be tied together into a workflow to accomplish a useful goal. We want to formally capture at least some of this knowledge within a virtual workbench and middleware framework to assist a wider range of biologists in utilizing these resources. Different activities require different representations of knowledge. Finding or substituting a service within a workflow is often best supported by a classification. Marshalling and configuring services is best accomplished using a formal description. Both representations are highly interdependent and maintaining consistency between the two by hand is difficult. We report on a description logic approach using the web ontology language DAML+OIL that uses property based service descriptions. The ontology is founded on DAML-S to dynamically create service classifications. These classifications are then used to support semantic service matching and discovery in a large grid based middleware project . We describe the extensions necessary to DAML-S in order to support bioinformatics service description; the utility of DAML+OIL in creating dynamic classifications based on formal descriptions; and the implementation of a DAML+OIL ontology service to support partial user-driven service matching and composition.

/pdf/a-suite-of-daml-oil-ontologies-to-describe-bioinformatics-2wwj5izjzw.pdf

A suite of daml+oil ontologies to describe bioinformatics web services and data

Life science researchers increasingly rely on the web as a primary source of data, forcing them to apply the same rigor to its use as to an experiment in the laboratory. The Grid project is developing the use of workflows to explicitly capture web-based procedures, and provenance to describe how and why results were produced. Experience within Grid has shown that this provenance metadata is formed from a complex web of heterogenous resources that impact on the production of a result. Therefore we have explored the use of Semantic Web technologies such as RDF, and ontologies to support its representation and used existing initiatives such as Jena and LSID, to generate and store such material. The effective presentation of complex RDF graphs is challenging. Haystack has been used to provide multiple views of provenance metadata that can be further annotated. This work therefore forms a case study showing how existing Semantic Web tools can effectively support the emerging requirements of life science research.

Using semantic web technologies for representing E-science provenance

The Gene Ontology Next Generation Project (GONG) is developing a staged methodology to evolve the current representation of the Gene Ontology into DAML+OIL in order to take advantage of the richer formal expressiveness and the reasoning capabilities of the underlying description logic. Each stage provides a step level increase in formal explicit semantic content with a view to supporting validation, extension and multiple classification of the Gene Ontology. The paper introduces DAML+OIL and demonstrates the activity within each stage of the methodology and the functionality gained.

/pdf/a-methodology-to-migrate-the-gene-ontology-to-a-description-3p7reh7sl7.pdf

Chris Wroe

Papers

Taverna: lessons in creating a workflow environment for the life sciences

OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns

A suite of daml+oil ontologies to describe bioinformatics web services and data

Using semantic web technologies for representing E-science provenance

A Methodology to Migrate the Gene Ontology to a Description Logic Environment Using DAML+OIL