A Life Cycle Approach to the Development and Validation of an Ontology of the U.S
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UNIVERSITY of CALGARY Concept-Learning Supported
UNIVERSITY OF CALGARY Concept-Learning Supported Semantic Search using Multi-Agent System by Cheng Zhong A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING CALGARY, ALBERTA April, 2009 © Cheng Zhong 2009 ISBN: 978-0-494-51171-8 UNIVERSITY OF CALGARY FACULTY OF GRADUATE STUDIES The undersigned certify that they have read, and recommend to the Faculty of Graduate Studies for acceptance, a thesis entitled "Concept-Learning Supported Semantic Search using Multi-Agent System" submitted by Cheng Zhong in partial fulfilment of the requirements of the degree of Master of Science. Supervisor, Dr. B. H. Far Department of Electrical and Computer Engineering Dr. M. Moussavi Department of Electrical and Computer Engineering Dr. D. Krishnamurthy Department of Electrical and Computer Engineering Dr. Y. Hu Department of Electrical and Computer Engineering Dr. M. Ghaderi Department of Computer Science Date ii Abstract Currently, the mainstream of semantic search is based on both centralized networking that could be barrier to access trillions of dynamically generated bytes on individual websites, and group commitment to a common ontology that is often too strong or unrealistic. In real world, it is preferred to enable stakeholders of knowledge to exchange information freely while they keep their own individual ontology. While this assumption makes stakeholders represent their knowledge more independently and gives them more flexibility, it brings complexity to the communication among them. To solve this communication complexity, in this thesis, we present (1) a method for semantic search supported by ontological concept learning, and (2) a prototype multi-agent system that can handle semantic search and encapsulate the complexity of such process from the users. -
Deep Semantics in the Geosciences: Semantic Building Blocks for a Complete Geoscience Infrastructure
Deep Semantics in the Geosciences: semantic building blocks for a complete geoscience infrastructure Brandon Whitehead,1,2 Mark Gahegan1 1Centre for eResearch 2 Institute of Earth Science and Engineering The University of Auckland, Private Bag 92019, Auckland, New Zealand {b.whitehead, m.gahegan}@auckland.ac.nz Abstract. In the geosciences, the semantic models, or ontologies, available are typically narrowly focused structures fit for single purpose use. In this paper we discuss why this might be, with the conclusion that it is not sufficient to use semantics simply to provide categorical labels for instances—because of the interpretive and uncertain nature of geoscience, researchers need to understand how a conclusion has been reached in order to have any confidence in adopting it. Thus ontologies must address the epistemological questions of how (and possibly why) something is ‘known’. We provide a longer justification for this argument, make a case for capturing and representing these deep semantics, provide examples in specific geoscience domains and briefly touch on a visualisation program called Alfred that we have developed to allow researchers to explore the different facets of ontology that can support them applying value judgements to the interpretation of geological entities. Keywords: geoscience, deep semantics, ontology-based information retrieval 1 Introduction From deep drilling programs and large-scale seismic surveys to satellite imagery and field excursions, geoscience observations have traditionally been expensive to capture. As such, many disciplines related to the geosciences have relied heavily on inferential methods, probability, and—most importantly—individual experience to help construct a continuous (or, more complete) description of what lies between two data values [1]. -
Functions in Basic Formal Ontology
Applied Ontology 11 (2016) 103–128 103 DOI 10.3233/AO-160164 IOS Press Functions in Basic Formal Ontology Andrew D. Spear a,∗, Werner Ceusters b and Barry Smith c a Philosophy Department, Grand Valley State University, 1 Campus Drive, Allendale, MI 49401, USA Tel.: +1 616 331 2847; Fax: +1 616 331 2601; E-mail: [email protected] b Departments of Biomedical Informatics and Psychiatry, University at Buffalo, 77 Goodell street, Buffalo, NY 14203, USA E-mail: [email protected] c Department of Philosophy, University at Buffalo, 135 Park Hall, Buffalo, NY 14260, USA E-mail: [email protected] Abstract. The notion of function is indispensable to our understanding of distinctions such as that between being broken and being in working order (for artifacts) and between being diseased and being healthy (for organisms). A clear account of the ontology of functions and functioning is thus an important desideratum for any top-level ontology intended for application to domains such as engineering or medicine. The benefit of using top-level ontologies in applied ontology can only be realized when each of the categories identified and defined by a top-level ontology is integrated with the others in a coherent fashion. Basic Formal Ontology (BFO) has from the beginning included function as one of its categories, exploiting a version of the etiological account of function that is framed at a level of generality sufficient to accommodate both biological and artifactual functions. This account has been subjected to a series of criticisms and refinements. We here articulate BFO’s account of function, provide some reasons for favoring it over competing views, and defend it against objections. -
A Definition of Ontological Category
Two Demarcation Problems In Ontology Pawel Garbacz Department of Philosophy John Paul II Catholic University of Lublin, Poland Abstract his or her research interests. Or if not, then everything goes into the scope. In this paper I will attempt to characterise the difference be- This paper is then about the proper subject matter of ap- tween ontological and non-ontological categories for the sake of a better understanding of the subject matter of ontology. plied ontology. I will attempt to draw a demarcation line My account of ontological categories defines them as equiva- between ontological and non-ontological categories. To this lence classes of a certain family of equivalence relations that end I will search for the proper level of generality of the lat- are determined by ontological relations. As a result, the de- ter by looking at how philosophical ontology defines its sub- marcation problem for ontological categories turns out to be ject matter. I will discuss a number of attempts to capture the dependent on the demarcation problem for ontological rela- specific nature of the ontological categories, as they are used tions. in philosophy, and on the basis of this survey I outline my own proposal. The main point of my contribution is the idea Introduction that ontological categories are the most general categories that cut the reality at its joints, where cutting is provided There are a lot of ontologies out there. (Ding et al., 2005) by ontological relations. In consequence it will turn out that claim to harvest from the Internet more than 300 000 Se- this account depends on how one can draw a demarcation mantic Web documents, of which 1.5% may be unique on- line between ontological and non-ontological relations. -
The Zebrafish Anatomy and Stage Ontologies: Representing the Anatomy and Development of Danio Rerio
Van Slyke et al. Journal of Biomedical Semantics 2014, 5:12 http://www.jbiomedsem.com/content/5/1/12 JOURNAL OF BIOMEDICAL SEMANTICS RESEARCH Open Access The zebrafish anatomy and stage ontologies: representing the anatomy and development of Danio rerio Ceri E Van Slyke1*†, Yvonne M Bradford1*†, Monte Westerfield1,2 and Melissa A Haendel3 Abstract Background: The Zebrafish Anatomy Ontology (ZFA) is an OBO Foundry ontology that is used in conjunction with the Zebrafish Stage Ontology (ZFS) to describe the gross and cellular anatomy and development of the zebrafish, Danio rerio, from single cell zygote to adult. The zebrafish model organism database (ZFIN) uses the ZFA and ZFS to annotate phenotype and gene expression data from the primary literature and from contributed data sets. Results: The ZFA models anatomy and development with a subclass hierarchy, a partonomy, and a developmental hierarchy and with relationships to the ZFS that define the stages during which each anatomical entity exists. The ZFA and ZFS are developed utilizing OBO Foundry principles to ensure orthogonality, accessibility, and interoperability. The ZFA has 2860 classes representing a diversity of anatomical structures from different anatomical systems and from different stages of development. Conclusions: The ZFA describes zebrafish anatomy and development semantically for the purposes of annotating gene expression and anatomical phenotypes. The ontology and the data have been used by other resources to perform cross-species queries of gene expression and phenotype data, providing insights into genetic relationships, morphological evolution, and models of human disease. Background function, development, and evolution. ZFIN, the zebrafish Zebrafish (Danio rerio) share many anatomical and physio- model organism database [10] manually curates these dis- logical characteristics with other vertebrates, including parate data obtained from the literature or by direct data humans, and have emerged as a premiere organism to submission. -
Introduction to Ontologies Part I
EMMC The European Materials Modelling Council Introduction to Ontologies Part I Alexandra Simperler On-line 29.4.2019 https://emmc.info/ EMMC The EMMO round table Emanuele Ghedini (University of Bologna) Gerhard Goldbeck Adham Hashibon (Goldbeck Consulting) (Fraunhofer Institut) Georg J. Schmitz Jesper Friis (Access) (SINTEF) EMMC Outline • Taxonomy vs Ontology • The value of ontologies • Semantic Technologies • Representation of Ontologies What’s the difference between an EMMC ontology and a taxonomy? TAXONOMY ONTOLOGY • Like a tree with branches • Like a spiderweb • Parent – Child relation, • Manifold of relations, is_a adds non is_a relations • Generally limited to a • Not limited to a specific specific subject area subject area • Hierarchy of (simple) • Complex relations with concepts complex concepts EMMC The Value of Semantic Technologies • Natural perspective of human communication • Greater expressivity than a database • Improved logical structure • Knowledge layer is separated from data layer • Flexibility, reusability, interoperability • Hierarchies, relationships and annotation • Search patterns can be stored, share, reused • Reasoning – answers to what-if, if-then questions • Accessible to Artificial Intelligence EMMC The Value of Ontology in the Materials Field Artificial Intelligence Materials Ontology will contribute to: Semantic Web Systems Engineering • High throughput experiments Biomedical Informatics • High throughput characterization Library Science • Cost reduction Enterprise Bookmarking Information Architecture • Reliable results • Standard operation procedures (SOPs) • Design of materials with improved characteristics All these fields create Ontologies to limit • Classification of techniques and complexity and acceleration of results organize information. The Ontology can then • Uniform query interface be applied to problem solving. EMMC Examples/Use of Ontologies • Database integration – Connected data! Discover new trends – Takahashi, et al (2018). -
GMS 6805: Introduction to Applied Ontology Location
GMS 6805: Introduction to Applied Ontology Location: Online, TBA Class Hours: Wednesdays 1:55-3:50 pm Instructor: Mathias Brochhausen, PhD Office: 3226, Clinical and Translational Science Building Email: [email protected] Phone: 501-831-3119 Office Hours: By Appointment Course Description: Applied ontology is a sub-discipline of knowledge representation that develops resources that make the meaning of terms processable by computers to improve interoperability of data and to support reasoning with digital knowledge bases. This course introduces students to the fundamentals of applied ontology and its role in biomedical informatics. Students will learn what ontologies are, how they differ from similar resources and how they are implemented in knowledge management environments. Course Prerequisites: None, but PHI 6105: Seminar in Logic, or experience with symbolic logic, is an asset. Course Objectives: • Describe the need for semantic integration of biomedical data • Identify the components of the Semantic Web technology and the goals of Semantic Web Technologies • Describe how ontologies fit into the Semantic Web paradigm and the role of Applied Ontology within in • Understand the computational principles behind ontology development and implementation • Describe how ontological artifacts differ terminologies and other semantic resources • Articulate standards and criteria for good ontologies and evaluate ontologies in light of these criteria • Illustrate common pitfalls of ontology development • Create a domain ontology in an ontology editor such as Protégé • Construct queries that demonstrate an understanding of the logical principles of ontologies and the Semantic Web Course Texts: Required Tests: Antoniou, G. (2012). A Semantic Web Primer. Cambridge, MA: The MIT Press. Arp, R. et al. -
Ontology, Ontologies, and Science
Ontology, Ontologies, and Science Gary H. Merrill This is the “final accepted version” of the manuscript, made publicly available in accord with the policies of SpringerNature. The final publication in the journal Topoi (April 2011, Volume 30, Issue 1, pp 71–83) is available via http://dx.doi.org/10.1007/s11245-011-9091-x ABSTRACT Philosophers frequently struggle with the relation of metaphysics to the everyday world, with its practical value, and with its relation to empirical science. This paper distinguishes several different models of the relation between philosophical ontology and applied (scientific) ontology that have been advanced in the history of philosophy. Adoption of a strong participation model for the philosophical ontologist in science is urged, and requirements and consequences of the participation model are explored. This approach provides both a principled view and justification of the role of the philosophical ontologist in contemporary empirical science as well as guidelines for integrating philosophers and philosophical contributions into the practice of science. Introduction Metaphysicians, when explaining or justifying their calling, tend to be a mournful and defensive lot while at the same time extolling the intellectual, moral, and spiritual virtues of metaphysics and its practice. A classic example is found in Russell's The Problems of Philosophy where he argues that philosophy as a discipline is not quite as fruitless as it may appear: Philosophy, like all other studies, aims primarily at knowledge.... But it cannot be maintained that philosophy has had any very great measure of success in its attempts to provide definite answers to its questions.... It is true that this is partly accounted for by the fact that as soon as definite knowledge concerning any subject becomes possible, this subject ceases to be called philosophy, and becomes a separate science... -
Human Disease Ontology 2018 Update: Classification, Content And
Published online 8 November 2018 Nucleic Acids Research, 2019, Vol. 47, Database issue D955–D962 doi: 10.1093/nar/gky1032 Human Disease Ontology 2018 update: classification, content and workflow expansion Lynn M. Schriml 1,*, Elvira Mitraka2, James Munro1, Becky Tauber1, Mike Schor1, Lance Nickle1, Victor Felix1, Linda Jeng3, Cynthia Bearer3, Richard Lichenstein3, Katharine Bisordi3, Nicole Campion3, Brooke Hyman3, David Kurland4, Connor Patrick Oates5, Siobhan Kibbey3, Poorna Sreekumar3, Chris Le3, Michelle Giglio1 and Carol Greene3 1University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA, 2Dalhousie University, Halifax, NS, Canada, 3University of Maryland School of Medicine, Baltimore, MD, USA, 4New York University Langone Medical Center, Department of Neurosurgery, New York, NY, USA and 5Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA Received September 13, 2018; Revised October 04, 2018; Editorial Decision October 14, 2018; Accepted October 22, 2018 ABSTRACT INTRODUCTION The Human Disease Ontology (DO) (http://www. The rapid growth of biomedical and clinical research in re- disease-ontology.org), database has undergone sig- cent decades has begun to reveal novel cellular, molecular nificant expansion in the past three years. The DO and environmental determinants of disease (1–4). However, disease classification includes specific formal se- the opportunities for discovery and the transcendence of mantic rules to express meaningful disease mod- knowledge between research groups can only be realized in conjunction with the development of rigorous, standard- els and has expanded from a single asserted clas- ized bioinformatics tools. These tools should be capable of sification to include multiple-inferred mechanistic addressing specific biomedical data nomenclature and stan- disease classifications, thus providing novel per- dardization challenges posed by the vast variety of biomed- spectives on related diseases. -
Ech-0205 V1.0 Linked Open Data
E-Government Standards Page 1 of 49 eCH-0205 Linked Open Data Name Linked Open Data eCH-number eCH-0205 Category Accessory Document Quality stage Defined Version 1.0 Status Approved Decision on 2018-03-06 Date of issue 2018-03-13 Replaces version - Requirements - Annexes - Languages English (original) Authors Members of the eCH Specialized Group “Open Government Data” Main Author: Beat Estermann, Berner Fachhochschule [email protected] For a list of further contributors, see Annex B. Editor / Distribution eCH registered association, Mainaustrasse 30, Postfach [P.O. Box], 8034 Zürich T 044 388 74 64, F 044 388 71 80 www.ech.ch / [email protected] eCH registered association www.ech.ch / [email protected] eCH-0205 Linked Open Data / 1.0 / Approved / 2018-03-13 E-Government Standards Page 2 of 49 Summary This document provides the Swiss Linked Data community with a shared vision of the state of linked open data publication in the public and heritage sectors in Switzerland and gives people who are new to the community a first overview of previous and ongoing activities in the area of data publication, data use, and know-how exchange. The document contains a short introduction to linked (open) data, gives a detailed account of what linked data publica- tion is about, provides an overview of the present state of linked data publication by Swiss public and heritage sector organizations, and presents a series of exemplary use cases that serve as test and study cases to tackle current challenges and demonstrate the usefulness of linked (open) data in practice. -
Ontology-Based Approach for Structural Design Considering Low Embodied Energy and Carbon
This is an Open Access document downloaded from ORCA, Cardiff University's institutional repository: http://orca.cf.ac.uk/73163/ This is the author’s version of a work that was submitted to / accepted for publication. Citation for final published version: Hou, Shangjie, Li, Haijiang and Rezgui, Yacine 2015. Ontology-based approach for structural design considering low embodied energy and carbon. Energy and Buildings 102 , pp. 75-90. 10.1016/j.enbuild.2015.04.051 file Publishers page: http://dx.doi.org/10.1016/j.enbuild.2015.04.051 <http://dx.doi.org/10.1016/j.enbuild.2015.04.051> Please note: Changes made as a result of publishing processes such as copy-editing, formatting and page numbers may not be reflected in this version. For the definitive version of this publication, please refer to the published source. You are advised to consult the publisher’s version if you wish to cite this paper. This version is being made available in accordance with publisher policies. See http://orca.cf.ac.uk/policies.html for usage policies. Copyright and moral rights for publications made available in ORCA are retained by the copyright holders. Accepted Manuscript Title: Ontology-based approach for structural design considering low embodied energy and carbon Author: Shangjie Hou Haijiang Li Yacine Rezgui PII: S0378-7788(15)00350-3 DOI: http://dx.doi.org/doi:10.1016/j.enbuild.2015.04.051 Reference: ENB 5843 To appear in: ENB Received date: 14-11-2014 Revised date: 21-4-2015 Accepted date: 28-4-2015 Please cite this article as: S. -
Introduction to Applied Ontology and Ontological Analysis
First Interdisciplinary Summer School on Ontological Analysis Introduction to Applied Ontology and Ontological Analysis Nicola Guarino National Research Council, Institute for Cognitive Science and Technologies (ISTC-CNR) Laboratory for Applied Ontology (LOA) www.loa.istc.cnr.it Applied Ontology: an emerging interdisciplinary area • Applied Ontology builds on philosophy, cognitive science, linguistics and logic with the purpose of understanding, clarifying, making explicit and communicating people's assumptions about the nature and structure of the world. • This orientation towards helping people understanding each other distinguishes applied ontology from philosophical ontology, and motivates its unavoidable interdisciplinary nature. ontological analysis: study of content (of these assumptions) as such (independently of their representation) 4 Ontological analysis and conceptual modeling Conceptual modeling is the activity of formally describing some aspects of the physical and social world around us for the purposes of understanding and communication (John Mylopoulos) Focusing on content Do we know what to REpresent? • First analysis, • THEN representation… Unfortunately, this is not the current practice… • Computer scientists have focused on the structure of representations and the nature of reasoning more than on the content of such representations Essential ontological promiscuity of AI: any agent creates its own ontology based on its usefulness for the task at hand (Genesereth and Nilsson 1987) No representation without ontological