OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows

Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and building biomedical ontologies requires flexible and versatile tools to manipulate them efficiently, in particular for enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language for automating the changes to be performed in an ontology. OPPL augments the ontologists’ toolbox by providing a more efficient, and less error-prone, mechanism for enriching a biomedical ontology than that obtained by a manual treatment. Results We present OPPL-Galaxy, a wrapper for using OPPL within Galaxy. The functionality delivered by OPPL (i.e. automated ontology manipulation) can be combined with the tools and workflows devised within the Galaxy framework, resulting in an enhancement of OPPL. Use cases are provided in order to demonstrate OPPL-Galaxy’s capability for enriching, modifying and querying biomedical ontologies. Conclusions Coupling OPPL-Galaxy with other bioinformatics tools of the Galaxy framework results in a system that is more than the sum of its parts. OPPL-Galaxy opens a new dimension of analyses and exploitation of biomedical ontologies, including automated reasoning, paving the way towards advanced biological data analyses

PatOMat - Versatile Framework for Pattern-Based Ontology Transformation

The purpose of the PatOMat transformation framework is to bridge between different modeling styles of web ontologies. We provide a formal model of pattern-based ontology transformation, explain its implementation in PatOMat, and manifest the flexibility of the framework on diverse use cases

OntoCheck: verifying ontology naming conventions and metadata completeness in Protégé 4

BACKGROUND: Although policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata completeness. This fact is at least partially due to missing or inappropriate tools. Software support can ease this situation and contribute to overall ontology consistency and quality by helping to enforce such conventions. OBJECTIVE: We provide a plugin for the Protégé Ontology editor to allow for easy checks on compliance towards ontology naming conventions and metadata completeness, as well as curation in case of found violations. IMPLEMENTATION: In a requirement analysis, derived from a prior standardization approach carried out within the OBO Foundry, we investigate the needed capabilities for software tools to check, curate and maintain class naming conventions. A Protégé tab plugin was implemented accordingly using the Protégé 4.1 libraries. The plugin was tested on six different ontologies. Based on these test results, the plugin could be refined, also by the integration of new functionalities. RESULTS: The new Protégé plugin, OntoCheck, allows for ontology tests to be carried out on OWL ontologies. In particular the OntoCheck plugin helps to clean up an ontology with regard to lexical heterogeneity, i.e. enforcing naming conventions and metadata completeness, meeting most of the requirements outlined for such a tool. Found test violations can be corrected to foster consistency in entity naming and meta-annotation within an artefact. Once specified, check constraints like name patterns can be stored and exchanged for later re-use. Here we describe a first version of the software, illustrate its capabilities and use within running ontology development efforts and briefly outline improvements resulting from its application. Further, we discuss OntoChecks capabilities in the context of related tools and highlight potential future expansions. CONCLUSIONS: The OntoCheck plugin facilitates labelling error detection and curation, contributing to lexical quality assurance in OWL ontologies. Ultimately, we hope this Protégé extension will ease ontology alignments as well as lexical post-processing of annotated data and hence can increase overall secondary data usage by humans and computers

The consistent representation of scientific knowledge : investigations into the ontology of karyotypes and mitochondria

PhD ThesisOntologies are widely used in life sciences to model scienti c knowledge. The engineering of these ontologies is well-studied and there are a variety of methodologies and techniques, some of which have been re-purposed from software engineering methodologies and techniques. However, due to the complex nature of bio-ontologies, they are not resistant to errors and mistakes. This is especially true for more expressive and/or larger ontologies. In order to improve on this issue, we explore a variety of software engineering techniques that were re-purposed in order to aid ontology engineering. This exploration is driven by the construction of two light-weight ontologies, The Mitochondrial Disease Ontology and The Karyotype Ontology. These ontologies have speci c and useful computational goals, as well as providing exemplars for our methodology. This thesis discusses the modelling decisions undertaken as well as the overall success of each ontological model. Due to the added knowledge capture steps required for the mitochondrial knowledge, The Karyotype Ontology is further developed than The Mitochondrial Disease Ontology. Speci cally, this thesis explores the use of a pattern-driven and programmatic approach to bio-medical ontology engineering. During the engineering of our biomedical ontologies, we found many of the components of each model were similar in logical and textual de nitions. This was especially true for The Karyotype Ontology. In software engineering a common technique to avoid replication is to abstract through the use of patterns. Therefore we utilised localised patterns to model these highly repetitive models. There are a variety of possible tools for the encoding of these patterns, but we found ontology development using Graphical User Interface (GUI) tools to be time-consuming due to the necessity of manual GUI interaction when the ontology needed updating. With the development of Tawny- OWL, a programmatic tool for ontology construction, we are able to overcome this issue, with the added bene t of using a single syntax to express both simple and - i - patternised parts of the ontology. Lastly, we brie y discuss how other methodologies and tools from software engineering, namely unit tests, di ng, version control and Continuous Integration (CI) were re-purposed and how they aided the engineering of our two domain ontologies. Together, this knowledge increases our understanding in ontology engineering techniques. By re-purposing software engineering methodologies, we have aided construction, quality and maintainability of two novel ontologies, and have demonstrated their applicability more generally

Knowledge Patterns for the Web: extraction, tranformation and reuse

This thesis aims at investigating methods and software architectures for discovering what are the typical and frequently occurring structures used for organizing knowledge in the Web. We identify these structures as Knowledge Patterns (KPs). KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Then we present K~ore, a software architecture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization

Data-Driven Methodology for Knowledge Graph Generation Within the Tourism Domain

The tourism and hospitality sectors have become increasingly important in the last few years and the companies operating in this field are constantly challenged with providing new innovative services. At the same time, (big-) data has become the “new oil” of this century and Knowledge Graphs are emerging as the most natural way to collect, refine, and structure this heterogeneous information. In this paper, we present a methodology for semi-automatic generating a Tourism Knowledge Graph (TKG), which can be used for supporting a variety of intelligent services in this space, and a new ontology for modelling this domain, the Tourism Analytics Ontology (TAO). Our approach processes and integrates data from Booking.com, Airbnb, DBpedia, and GeoNames. Due to its modular structure, it can be easily extended to include new data sources or to apply new enrichment and refinement functions. We report a comprehensive evaluation of the functional, logical, and structural dimensions of TKG and TAO

Ontologie-gestützte Optimierung des Entwurfs automobilelektronischer Systeme

Die zu beherrschende Komplexität bei der Entwicklung automobilelektronischer Systeme unterliegt einem stetigen Wachstum und ist nicht zuletzt aus diesem Grund mit mehreren ingenieurtechnischen Herausforderungen verbunden. Etablierte Ansätze wie die des Systems Engineering bieten Möglichkeiten, solch komplexe Systeme zu entwerfen und schließlich zu realisieren. Vordringliches Problem in diesem Zusammenhang ist jedoch, dass Engineering-Daten primär in über unterschiedliche Arbeitsplatzsysteme verstreuten Dokumenten abgelegt sind und dass diese nur unzureichend verwaltet werden. Einen Ausweg aus dieser Misere stellt die Abbildung dieser Daten auf Modelle dar. So gilt das Modell-basierte Systems Engineering derweil in der Automobil- und Luftfahrtindustrie als akzeptierter Weg, komplexe Systeme zu realisieren, auch wenn nicht alle Disziplinen dabei kontinuierlich gekoppelt sind. Nicht nur für diese Kopplung, sondern auch für das automatische Schlussfolgern benötigen Modelle zusätzliche, explizite Semantik. Automatisches Schlussfolgern ist beispielsweise für die Identifikation von Korrelationen zwischen Systems Engineering-Daten erforderlich. Für die Schaffung semantischer Interoperabilität eignen sich insbesondere Ontologien, die selbst auch Modelle sind. In dieser Arbeit wird ein Ontologie-basierter Ansatz zur Optimierung des Entwurfsprozesses von automobilelektronischen Systemen vorgestellt. Wesentlicher Grundgedanke dabei ist es, Ontologien zu nutzen, um Entwurfsmethoden und -modelle zu konsolidieren und zu integrieren. Dazu beruht der Ansatz im Kern auf dem Vorschlag einer einheitlichen Basis zur Entwicklung und Ausführung von Anwendungen, unter konsequenter Nutzung etablierter Standards, um Modelle auf Ontologien abzubilden. Diese Basis wurde als Softwareplattform realisiert, welche unter anderem auf eine nahtlose Integration in existierende Arbeitsabläufe abzielt. Vorrangiger Aspekt des Lösungsansatzes ist die Berücksichtigung von Anforderungen, sowie spezieller Last- und Nutzungsprofilen in Form von sogenannten Mission Profiles und deren Integration in Entwicklungsprozesse. Ergänzt wird diese Arbeit zudem durch die Beschreibung und Einordnung dreier Anwendungen, welche auf der Plattform aufsetzen und zur Untersuchung und Bewertung in konkreten Fallbeispielen Gebrauch finden. Die damit entstandenen Entwurfsmethodiken adressieren jeweils spezielle Problemstellungen aus dem Umfeld der Entwicklung automobilelektronischer Systeme und demonstrieren zudem die Anwendbarkeit der vorgestellten Entwurfs- und Anwendungsplattform

Interactive Learning of Probabilistic Decision Making by Service Robots with Multiple Skill Domains

This thesis makes a contribution to autonomous service robots, centered around two aspects. The first is modeling decision making in the face of incomplete information on top of diverse basic skills of a service robot. Second, based on such a model, it is investigated, how to transfer complex decision-making knowledge into the system. Interactive learning, naturally from both demonstrations of human teachers and in interaction with objects, yields decision-making models applicable by the robot

A Holmes and Doyle Bibliography, Volume 9: All Formats—Combined Alphabetical Listing

This bibliography is a work in progress. It attempts to update Ronald B. De Waal’s comprehensive bibliography, The Universal Sherlock Holmes, but does not claim to be exhaustive in content. New works are continually discovered and added to this bibliography. Readers and researchers are invited to suggest additional content. This volume contains all listings in all formats, arranged alphabetically by author or main entry. In other words, it combines the listings from Volume 1 (Monograph and Serial Titles), Volume 3 (Periodical Articles), and Volume 7 (Audio/Visual Materials) into a comprehensive bibliography. (There may be additional materials included in this list, e.g. duplicate items and items not yet fully edited.) As in the other volumes, coverage of this material begins around 1994, the final year covered by De Waal's bibliography, but may not yet be totally up-to-date (given the ongoing nature of this bibliography). It is hoped that other titles will be added at a later date. At present, this bibliography includes 12,594 items