A survey on units ontologies: architecture, comparison and reuse

Purpose With the increasing spread of ontologies in various domains, units have gradually become an essential part of ontologies and units ontologies have been developed to offer a better expression ability for the practical usage. From the perspectives of architecture, comparison and reuse, the purpose of this paper is to provide a comprehensive survey on four mainstream units ontologies: quantity-unit-dimension-type, quantities, units, dimensions and values, ontology of units of measure and units ontology (UO) of the open biomedical ontologies, in order to address well the state of the art and the reuse strategies of the UO. Design/methodology/approach An architecture of units ontologies is presented, in which the relations between key factors (i.e. units of measure, quantity and dimension) are discussed. The criteria for comparing units ontologies are developed from the perspectives of organizational structure, pattern design and application scenario. Then, the authors compare four typical units ontologies based on the proposed comparison criteria. Furthermore, how to reuse these units ontologies is discussed in materials science domain by utilizing two reuse strategies of partial reference and complete reference. Findings Units ontologies have attracted high attention in the scientific domain. Based on the comparison of four popular units ontologies, this paper finds that different units ontologies have different design features from the perspectives of basis structure, units conversion and axioms design; a UO is better to be applied to the application areas that satisfy its design features; and many challenges remain to be done in the future research of the UO. Originality/value This paper makes an extensive review on units ontologies, by defining the comparison criteria and discussing the reuse strategies in the materials domain. Based on this investigation, guidelines are summarized for the selection and reuse of units ontologies.

[1]  Jessica A. Turner,et al.  The Cognitive Paradigm Ontology: Design and Application , 2011, Neuroinformatics.

[2]  John Sidney,et al.  An ontology for major histocompatibility restriction , 2016, Journal of Biomedical Semantics.

[3]  Dieter Fensel,et al.  Knowledge Engineering: Principles and Methods , 1998, Data Knowl. Eng..

[4]  Robert G. Raskin,et al.  Knowledge representation in the semantic web for Earth and environmental terminology (SWEET) , 2005, Comput. Geosci..

[5]  Narain H. Gehani,et al.  Units of Measure as a Data Attribute , 1977, Comput. Lang..

[6]  Dympna O'Sullivan,et al.  An Ontology-Driven Information Model for Interoperability of Personal and Electronic Health Records , 2014, eTELEMED 2014.

[7]  Jiao Tao,et al.  Integrity Constraints in OWL , 2010, AAAI.

[8]  N Graf,et al.  p-Medicine: From data sharing and integration via VPH models to personalized medicine , 2011, Ecancermedicalscience.

[9]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[10]  Barry N. Taylor,et al.  Guide for the Use of the International System of Units (SI) , 1995 .

[11]  Klaus Knorr,et al.  International System , 2019 .

[12]  Bin Chen,et al.  The ChEMBL database as linked open data , 2013, Journal of Cheminformatics.

[13]  Cees T. A. M. de Laat,et al.  The NOVI information models , 2015, Future Gener. Comput. Syst..

[14]  Jane Hunter,et al.  MatSeek: An Ontology-Based Federated Search Interface for Materials Scientists , 2009, IEEE Intelligent Systems.

[15]  Hajo Rijgersberg,et al.  Ontology of units of measure and related concepts , 2013, Semantic Web.

[16]  B. A. Simonsa,et al.  Defining a water quality vocabulary using QUDT and ChEBI , 2013 .

[17]  A. Déom,et al.  [The international system of units (SI)]. , 1979, Zeitschrift fur Krankenpflege. Revue suisse des infirmieres.

[18]  C. Muntean,et al.  An overview of ontologies and knowledge management. , 2010 .

[19]  Xiaoming Zhang,et al.  A survey on knowledge representation in materials science and engineering: An ontological perspective , 2015, Comput. Ind..

[20]  Mohammed Bennamoun,et al.  Ontology learning from text: A look back and into the future , 2012, CSUR.

[21]  K. Bretonnel Cohen,et al.  Text mining for the biocuration workflow , 2012, Database J. Biol. Databases Curation.

[22]  Jan Top,et al.  Tiffany: sharing and managing knowledge in food science , 2008 .

[23]  Hajo Rijgersberg,et al.  How semantics can improve engineering processes: A case of units of measure and quantities , 2011, Adv. Eng. Informatics.

[24]  Jens Lehmann,et al.  Class expression learning for ontology engineering , 2011, J. Web Semant..

[25]  Adam Pease,et al.  The Suggested Upper Merged Ontology: A Large Ontology for the Semantic Web and its Applic ations , 2002 .

[26]  Chen Jie,et al.  Overview of Ontology , 2002 .

[27]  Xiaoming Zhang,et al.  STSM: An Infrastructure for Unifying Steel Knowledge and Discovering New Knowledge , 2014 .

[28]  Chau Do,et al.  Using MathML to Represent Units of Measurement for Improved Ontology Alignment , 2013, MKM/Calculemus/DML.

[29]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[30]  Jane Hunter,et al.  The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain , 2011, BMC Bioinformatics.

[31]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .

[32]  Zoran Budimac,et al.  An overview of ontologies and data resources in medical domains , 2014, Expert Syst. Appl..

[33]  Marcus P. Foster Quantities, units and computing , 2013, Comput. Stand. Interfaces.

[34]  Toshihiro Ashino,et al.  Materials Ontology: An Infrastructure for Exchanging Materials Information and Knowledge , 2010, Data Sci. J..

[35]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[36]  Simon Cox,et al.  A Harmonized Vocabulary For Water Quality , 2014 .

[37]  Helena Sofia Pinto,et al.  Revising and extending the Units of Measure “ subontology ” , 2007 .

[38]  Aldo Gangemi,et al.  Ontology Design Patterns , 2005 .

[39]  Xiaojing Wang,et al.  Corrigendum: Proteomic analysis of colon and rectal carcinoma using standard and customized databases , 2015, Scientific Data.

[40]  Charalampos Bratsas,et al.  Towards exergaming commons: composing the exergame ontology for publishing open game data , 2016, Journal of Biomedical Semantics.

[41]  Cui Tao,et al.  A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data , 2013, J. Am. Medical Informatics Assoc..

[42]  Rafael Peñaloza,et al.  Context-dependent views to axioms and consequences of Semantic Web ontologies , 2012, J. Web Semant..

[43]  Paul N. Schofield,et al.  The Units Ontology: a tool for integrating units of measurement in science , 2012, Database J. Biol. Databases Curation.

[44]  James A. Hendler,et al.  The Semantic Web" in Scientific American , 2001 .

[45]  Jens Lehmann,et al.  Universal OWL Axiom Enrichment for Large Knowledge Bases , 2012, EKAW.

[46]  George Papadatos,et al.  A large-scale crop protection bioassay data set , 2015, Scientific Data.

[47]  Gregory R. Olsen,et al.  An Ontology for Engineering Mathematics , 1994, KR.