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A Multi-strategy Approach for Ontology Reuse Through Matching and Integration Techniques

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Quality Software Through Reuse and Integration (FMI 2016, IRI 2016 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 561))

Abstract

The new revolutionary web today, the Semantic Web, has augmented the previous one by promoting common data formats and exchange protocols in order to provide a framework that allows data to be shared and reused across application, enterprise, and community boundaries. This revolution, together with the increasing digitization of the world, has led to a high availability of knowledge models, i.e., more or less formal representations of concepts underlying a certain universe of discourse, which span throughout a wide range of topics, fields of study and applications, mostly heterogeneous from each other at a different dimensions. As more and more outbreaks of this new revolution light up, a major challenge came soon into sight: addressing the main objectives of the semantic web, the sharing and reuse of data, demands effective and efficient methodologies to mediate between models speaking different languages. Since ontologies are the de facto standard in representing and sharing knowledge models over the web, this paper presents a comprehensive methodology to ontology integration and reuse based on various matching techniques. The approach proposed here is supported by an ad hoc software framework whose scope is easing the creation of new ontologies by promoting the reuse of existing ones and automatizing, as much as possible, the whole ontology construction procedure.

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Notes

  1. 1.

    scholar.py, A parser for Google Scholar, written in Python. Available online: https://github.com/ckreibich/scholar.py.

  2. 2.

    National Cancer Institute Thesaurus. Available online, https://ncit.nci.nih.gov/ncitbrowser/.

  3. 3.

    AGROVOC Multilingual agricultural thesaurus. Available online, http://aims.fao.org/vest-registry/vocabularies/agrovoc-multilingual-agricultural-thesaurus.

  4. 4.

    Linked Recipe Schema. Available online, http://aims.fao.org/vest-registry/vocabularies/agrovoc-multilingual-agricultural-thesaurus.

  5. 5.

    BBC Food Ontology. Available online, http://www.bbc.co.uk/ontologies/fo.

  6. 6.

    LIRMM Food Ontology. Available online, http://data.lirmm.fr/ontologies/food.

  7. 7.

    The Product Types Ontology. Available online, http://www.productontology.org/.

  8. 8.

    Oregon State Food Glossary. Available online, http://icbo.cgrb.oregonstate.edu/node/282.

  9. 9.

    Eurocode 2 Food Coding System. Available online, http://www.danfood.info/eurocode/.

  10. 10.

    WAND Food and Beverage Taxonomy. Available online, http://www.wandinc.com/wand-food-and-beverage-taxonomy.aspx.

  11. 11.

    International classification for Standards (ISC). Available online, http://www.iso.org/iso/home/store/catalogue_ics.htm.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Information Technologies, University of Naples, Federico II, Napoli, Italy

    Enrico G. Caldarola & Antonio M. Rinaldi

  2. Institute of Industrial Technologies and Automation, National Research Council, Bari, Italy

    Enrico G. Caldarola

  3. IKNOS-LAB Intelligent and Knowledge Systems, LUPT - University of Naples, Federico II, Napoli, Italy

    Antonio M. Rinaldi

Authors
  1. Enrico G. Caldarola
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Corresponding author

Correspondence to Antonio M. Rinaldi .

Editor information

Editors and Affiliations

  1. SPAWAR Systems Center Pacific, San Diego, California, USA

    Stuart H. Rubin

  2. Laboratoire de Communication dans les Systèmes Informatiques, Ecole nationale Supérieure d’Informatique, Algiers, Algeria

    Thouraya Bouabana-Tebibel

A Appendix

A Appendix

The list below provides a short description for each selected reference model filtered out from the corpus of retrieved references.

  1. 1.

    National Cancer Institute Thesaurus Footnote 2 by the American National Institutes of Health (NIH):

    The NCI Thesaurus is a reference terminology and biomedical ontology used in NCI systems. It covers vocabulary for clinical care, translational and basic research, and public information and administrative activities. It contains 118941 classes, 46839 individuals, 173 properties, 16 as the max depth, 3235 children, an average number of children equal to 6 and 36013 classes with no definitions

  2. 2.

    AGROVOC Multilingual agricultural thesaurus Footnote 3 by AIMS Advisory Board:

    AGROVOC is a controlled vocabulary covering all areas of interest of the Food and Agriculture Organization (FAO) of the United Nations, including food, nutrition, agriculture, fisheries, forestry, environment etc. AGROVOC consists of over 32,000 concepts available in 27 languages: Arabic, Burmese, Chinese, Czech, English, French, German, Hindi, Hungarian, Italian, Japanese, Khmer, Korean, Lao, Malay, Moldovian, Persian, Polish, Portuguese, Russian, Slovak, Spanish, Telugu, Thai, Turkish, Ukrainian, Vientamese.

  3. 3.

    Linked Recipe Schema Footnote 4 by schema.org:

    Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond. These vocabularies cover entities, relationships between entities and actions, and can easily be extended through a well-documented extension model.

  4. 4.

    BBC Food Ontology Footnote 5 by BBC:

    The Food Ontology is a simple lightweight ontology for publishing data about recipes, including the foods they are made from and the foods they create as well as the diets, menus, seasons, courses and occasions they may be suitable for. Whilst it originates in a specific BBC use case, the Food Ontology should be applicable to a wide range of recipe data publishing across the web. It presents 57 named classes.

  5. 5.

    LIRMM Food Ontology Footnote 6 by LIRMM Laboratoire:

    This ontology models the Food domain. It allows to describe ingredients and food products. Some classes are: food:Recipe, food:Food, food:FoodProduct, food:Dish, food:Ingredient, etc.

  6. 6.

    The Product Types Ontology Footnote 7 by E-Business and Web Science Research Group at Bundeswehr University Munich:

    This ontology contains 300,000 precise definitions for types of product or services that extend the schema.org and GoodRelations standards for e-commerce markup.

  7. 7.

    Oregon State Food Glossary Footnote 8 by Oregon State University:

    FoodON is a new ontology built to interoperate with the OBO Library and to represent entities which bear a “food role”. It encompasses materials in natural ecosystems and food webs as well as human-centric categorization and handling of food.

  8. 8.

    Eurocode 2 Food Coding System Footnote 9 by European FLAIR Eurofoods-Enfant Project:

    The Eurocode 2 Food Coding System was originally developed within the European FLAIR Eurofoods-Enfant Project to serve as a standard instrument for nutritional surveys in Europe and to serve the need for food intake comparisons. It contains 162 named classes.

  9. 9.

    WAND Food and Beverage Taxonomy Footnote 10 by WAND Company:

    The WAND Food and Beverage Taxonomy includes 1,278 terms including foods, beverages, ingredients, and additives. This taxonomy includes anything that somebody may consume as food, including some prepared foods. The WAND Foods and Beverages Taxonomy is ideal for restaurants, groceries, and food manufacturers.

  10. 10.

    Food technology ISO Standard Footnote 11 by ISO:

    International standard by ISO which provides a terminology for processes in the food industry, including food hygiene and food safety, food products in general, methods of tests and analysis for food ICS (International Classification for Standards) products, materials and articles in contact with foodstuffs and materials and articles in contact with drinking water, plants and equipment for the food industry.

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Caldarola, E.G., Rinaldi, A.M. (2018). A Multi-strategy Approach for Ontology Reuse Through Matching and Integration Techniques. In: Rubin, S., Bouabana-Tebibel, T. (eds) Quality Software Through Reuse and Integration. FMI IRI 2016 2016 2016. Advances in Intelligent Systems and Computing, vol 561. Springer, Cham. https://doi.org/10.1007/978-3-319-56157-8_4

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