Searching Ontologies Based on Content: Experiments in the Biomedical Domain

As more ontologies become publicly available, finding the "right" ontologies becomes much harder. In this paper, we address the problem of ontology search: finding a collection of ontologies from an ontology repository that are relevant to the user's query. In particular, we look at the case when users search for ontologies relevant to a particular topic (e.g., an ontology about anatomy). Ontologies that are most relevant to such query often do not have the query term in the names of their concepts (e.g., the Foundational Model of Anatomy ontology does not have the term "anatomy" in any of its concepts' names). Thus, we present a new ontology-search technique that helps users in these types of searches. When looking for ontologies on a particular topic (e.g., anatomy), we retrieve from the Web a collection of terms that represent the given domain (e.g., terms such as body, brain, skin, etc. for anatomy). We then use these terms to expand the user query. We evaluate our algorithm on queries for topics in the biomedical domain against a repository of biomedical ontologies. We use the results obtained from experts in the biomedical-ontology domain as the gold standard. Our experiments demonstrate that using our method for query expansion improves retrieval results by a 113%, compared to the tools that search only for the user query terms and consider only class and property names (like Swoogle). We show 43% improvement for the case where not only class and property names but also property values are taken into account

Representation and validation of domain and range restrictions in a relational database driven ontology maintenance system

An ontology can be used to represent and organize the objects, properties, events, processes, and relations that embody an area of reality [1]. These knowledge bases may be created manually (by individuals or groups), and/or automatically using software tools, such as those developed for information retrieval and data mining. Recently, the National Science Foundation funded a large collaborative development project for the semi-automated construction of an ontology of amphibian anatomy (AmphibAnat [2]). To satisfy the extensive community curation requirements of that project, a generic, Web-based, multi-user, relational database ontology management system (RDBOM [3]) was constructed, based upon a novel theoretical ontology model called an Ontology Abstract Machine (OAM [4]). The need to support concurrent data entry by multiple users with different levels of access privileges (as determined and assigned by the administrators), made it critical to ensure that the entered data were semantically correct. In particular, the ability to define and enforce restrictions on property characteristics such as the domain and range of a relation provide several advantages. It helps to identify inconsistencies in the ontology, maintain a higher level of overall integrity, and avoid erroneous conclusions that could be made by automated reasoners. In this thesis a modified OAM model is presented that includes definitions for property characteristics and the associated validation algorithms. As proof of concept, it is shown how this modified abstract model has been implemented for domain and range restrictions in RDBOM --Abstract, page iii

From Natural Language Requirements to Formal Specification Using an Ontology

In order to check requirement specifications written in natural language, we have chosen to model domain knowledge through an ontology and to formally represent user requirements by its population. Our approach of ontology population focuses on instance property identification from texts. We do so using extraction rules automatically acquired from a training corpus and a bootstrapping terminology. These rules aim at identifying instance property mentions represented by triples of terms, using lexical, syntactic and semantic levels of analysis. They are generated from recurrent syntactic paths between terms denoting instances of concepts and properties. We show how focusing on instance property identification allows us to precisely identify concept instances explicitly or implicitly mentioned in texts

Exploring the boundaries and ontology of Psychiatric Disorders (PDs) using the Homeostatic Property Cluster (HPC) model

In this article we show that, even though the classification and diagnosis of Psychiatric Disorders (PDs) are performed according to essentialist terms, the psychiatric diagnoses currently employed, (i.e., clinical psychiatry) do not actually meet these criteria. Diagnosis is performed operationally. In this paper, we suggest a change of perspective. We reject essentialism relating to PDs and argue for the Homeostatic Property Cluster (HPC) model, which allows a greater insight into the ontology of PDs than the operational perspective. More specifically, we argue that the HPC model allows for a synthesis of continuous and discrete methods of understanding the boundaries between PDs. Finally, we specify in a more general manner, the kind of ontology we deal with when adopting the HPC model, arguing that this model can be viewed as a mirror device, reflecting the ontological features of PDs.In this article we show that, even though the classification and diagnosis of Psychiatric Disorders (PDs) are performed according to essentialist terms, the psychiatric diagnoses currently employed, (i.e., clinical psychiatry) do not actually meet these criteria. Diagnosis is performed operationally. In this paper, we suggest a change of perspective. We reject essentialism relating to PDs and argue for the Homeostatic Property Cluster (HPC) model, which allows a greater insight into the ontology of PDs than the operational perspective. More specifically, we argue that the HPC model allows for a synthesis of continuous and discrete methods of understanding the boundaries between PDs. Finally, we specify in a more general manner, the kind of ontology we deal with when adopting the HPC model, arguing that this model can be viewed as a mirror device, reflecting the ontological features of PDs

Functional Dependencies in OWL ABox

Functional Dependency (FD) has been extensively studied in database theory. Most recently there have been some works investigating the implications of extending Description Logics with functional dependencies. In particular the OWL ontology language offers the functional property property allowing simple functional dependency to be specified. As it turns out, more complex FD specified as concept constructors has been proved to lead to undecidability in the general case, which restricts its usage as part of TBOX. This paper departs from previous ones by restricting FDs applicability to instances in the ABOX. We specify FD as a new constructor, an OWL concept. FD instances are mapped to Horn clauses and evaluated against the ABOX according to user’s desired behavior. The latter allows users to determine whether FDs should be interpreted as constraints, assertions or views. Our approach gives ontology users data guarantees usually found in databases, integrated with the ontology conceptual model

Visualising product-service system business models

Copyright © 2014. Copyright in each paper in this conference’s proceedings is the property of the author(s). Permission is granted to reproduce copies of these works for purposes relevant to the above conference, provided that the author(s), source and copyright notice are included on each copy. For other uses, including extended quotation, please contact the author(s).The paper addresses the issue of how to visualise innovative business models at various stages of the design and development process. The focus is on a particular type of business model, defined Product-Service Systems (PSSs), characterised by an integrated product-service offering, but can be generalised to other business model innovations. The paper presents a visualisation system based on a formalised business model ontology and a set of visualisation tools, and discusses how it can be used to enhance internal and external communication and improve dialogue and co-design activities inside the company and with external stakeholders

New dimension in relational database preservation : raising the abstraction level

The work addressed in this paper focuses on the preserva- tion of the conceptual model within a specific class of dig- ital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform inde- pendence and to achieve a standard format in the digital preservation of relational databases, both data and struc- ture (logical model). Currently, in this project, we address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation ”property”. For the representation of this higher layer of abstraction present in databases we use an ontology based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that we tentatively represent using ”Web Ontology Language” (OWL). We developed a proto- type (supported by case study) and define a mapping algo- rithm for the conversion between the database and OWL. The ontology approach is adopted to formalize the knowl- edge associated to the conceptual model of the database and also a methodology to create an abstract representation of it

Resemblance, Exemplification, and Ontology

According to the quantificational (neo-) Quinean model in meta-ontology, the question of ontology boils down to the question of whether a sortal property is exemplified. I address some complications that arise when we try to build a philosophical reconstruction of the link between individuals and kinds displayed in the exemplification relation from the point of view of conceptualism about kinds and having in mind this stand in ontology. I distinguish two notions of resemblance, object-to- object and object-to- kind, and show the problems with both of them. Finally, I argue for a better awareness of the implicit "bias" involved in the very notion of "resemblance, " without indulging in Quine's veto toward this notion

The CIDOC CRM, an Ontological Approach to Schema Heterogeneity

The CIDOC Conceptual Reference Model (CRM), now ISO/CD21127, is a core ontology that aims at enabling information exchange and integration between heterogeneous sources of cultural heritage information, archives and libraries. It provides semantic definitions and clarifications needed to transform disparate, heterogeneous information sources into a coherent global resource, be it within a larger institution, in intranets or on the Internet. It is argued that such an ontology is property-centric, compact and highly generic, in contrast to terminological systems. The presentation will demonstrate how such a well-crafted core ontology can help to achieve a very high precision of schema integration at reasonable cost in a huge, diverse domain. It is further argued that such ontologies are widely reusable and adaptable to other domains which makes their development cost effective