Reusing and Re-engineering Non-ontological Resources for Building Ontologies

Villazón-Terrazas, Boris; Gómez-Pérez, Asuncíon

doi:10.1007/978-3-642-24794-1_6

Cited by 18 publications

(21 citation statements)

References 13 publications

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“… The Offer-job and Classification ontologies [18], to cover concepts of size, and domain of an organization.  The OntoiStar+ ontology [19], which contains concepts the i* framework.…”

Section: 2mentioning

confidence: 99%

A Catalogue of Reusable Context Model Elements Based on the i* Framework

Abad

Pérez

Carvallo

et al. 2017

Conceptual Modeling

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Abstract. The definition of system contexts is one of the most relevant activities in early phases of requirements engineering. It allows system engineers to narrow the system scope, by defining well established system boundaries. In practice, outlining a system context is cumbersome. In order to support this process, in this paper we propose a catalogue of context models elements expressed in i*, which can be reused as building blocks in the construction of context models for new systems. We describe the process used for the identification of a set of actors and dependencies recurrently appearing in several academic and industrial cases, and the process to store them into a catalogue of reusable i* context dependencies. The paper also illustrates possible cases of instantiation, to reuse them as patterns or context models chunks, which can be parametrized in relation to a given domain, with the support of a tool specifically designed for this purpose.

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“… The Offer-job and Classification ontologies [18], to cover concepts of size, and domain of an organization.  The OntoiStar+ ontology [19], which contains concepts the i* framework.…”

Section: 2mentioning

confidence: 99%

A Catalogue of Reusable Context Model Elements Based on the i* Framework

Abad

Pérez

Carvallo

et al. 2017

Conceptual Modeling

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“…The codebook was specified in semi-formal structured natural language designed for human consumption. While a common approach in social sciences it is not often studied in ontology engineering, e.g the methodology for ontology reengineering from non-ontological resources [3] doesn't consider it. 2.…”

Section: Background -Seshat: the Global History Databankmentioning

confidence: 99%

“…In addition it is desired to publish the dataset as linked data to enable other scholars to build upon the Seshat work. The new tools will be RDF-based using the Dacura data curation platform developed at Trinity College Dublin 2 as part of the ALIGNED H2020 project 3 . This paper investigates the research question: what is a suitable structure in RDF to represent the Seshat codebook that will support data quality assurance?…”

Section: Introductionmentioning

confidence: 99%

Building the Seshat Ontology for a Global History Databank

Brennan

Feeney

Mendel-Gleason

et al. 2016

The Semantic Web. Latest Advances and New Domains

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Abstract. This paper describes OWL ontology re-engineering from the wikibased social science codebook (thesaurus) developed by the Seshat: Global History Databank. The ontology describes human history as a set of over 1500 time series variables and supports variable uncertainty, temporal scoping, annotations and bibliographic references. The ontology was developed to transition from traditional social science data collection and storage techniques to an RDF-based approach. RDF supports automated generation of high usability data entry and validation tools, data quality management, incorporation of facts from the web of data and management of the data curation lifecycle.This ontology re-engineering exercise identified several pitfalls in modelling social science codebooks with semantic web technologies; provided insights into the practical application of OWL to complex, real-world modelling challenges; and has enabled the construction of new, RDF-based tools to support the large-scale Seshat data curation effort. The Seshat ontology is an exemplar of a set of ontology design patterns for modelling unncertainty or temporal bounds in standard RDF. Thus the paper provides guidance for deploying RDF in the social sciences. Within Seshat, OWL-based data quality management will assure the data is suitable for statistical analysis. Publication of Seshat as highquality, linked open data will enable other researchers to build on it.

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“…On a broader scope, the research in [25] provides the most recent and comprehensive survey of methods and tools for the refactoring of most types of non-ontological resources (NORs) into ontological resources (ORs), i.e. Web ontologies.…”

Section: Related Workmentioning

confidence: 99%

PCS2OWL: A Generic Approach for Deriving Web Ontologies from Product Classification Systems

Stolz

Rodriguez-Castro²,

Radinger

et al. 2014

Lecture Notes in Computer Science

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Abstract. The classification of products and services enables reliable and efficient electronic exchanges of product data across organizations. Many companies classify products (a) according to generic or industryspecific product classification standards, or (b) by using proprietary category systems. Such classification systems often contain thousands of product classes that are updated over time. This implies a large quantity of useful product category information for e-commerce applications on the Web of Data. Thus, instead of building up product ontologies from scratch, which is costly, tedious, error-prone, and high-maintenance, it is generally easier to derive them from existing classifications. In this paper, we (1) describe a generic, semi-automated method for deriving OWL ontologies from product classification standards and proprietary category systems. Moreover, we (2) show that our approach generates logically and semantically correct vocabularies, and (3) present the practical benefit of our approach. The resulting product ontologies are compatible with the GoodRelations vocabulary for e-commerce and with schema.org and can be used to enrich product and offer descriptions on the Semantic Web with granular product type information from existing data sources.

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Reusing and Re-engineering Non-ontological Resources for Building Ontologies

Cited by 18 publications

References 13 publications

A Catalogue of Reusable Context Model Elements Based on the i* Framework

A Catalogue of Reusable Context Model Elements Based on the i* Framework

Building the Seshat Ontology for a Global History Databank

PCS2OWL: A Generic Approach for Deriving Web Ontologies from Product Classification Systems

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