International Journal of Metadata, Semantics and Ontologies (7 papers in press)
Toward an international health workforce data standard: an analysis of regulatory agency documents
by Amy Opalek, Jane Greenberg
Abstract: Agencies responsible for regulating health professionals require detailed data describing individual practitioners and their qualifications. Initial collection of these data allows agencies to determine whether health professionals are qualified to practice safely. Ongoing collection of practitioner data is also critical for ensuring an adequate supply of health workers. A metadata standard facilitating data sharing among regulatory agencies can support these needs, providing the infrastructure necessary for detailed, interoperable practitioner registries. This paper presents the results of a document analysis of application forms used by 20 international agencies to collect data about physicians seeking licensure/registration. This research yielded over 250 unique data elements in 15 categories of interest. Though the scope of data required by regulatory agencies is vast, this research revealed a set of common metadata properties that provided a base for an international standard to support interoperable registries and the global exchange of health practitioner data.
Keywords: international data standards; health workforce; interoperability; metadata standards; document analysis; medical regulatory authorities; practitioner registries; metadata; professional licensure; professional registration.
Cross-querying LOD datasets using complex alignments: an experiment using AgronomicTaxon, Agrovoc, DBpedia and TAXREF-LD.
by Elodie Thieblin, Nathalie Hernandez, Catherine Roussey, Cassia Trojahn
Abstract: An increasing amount of datasets have being published on the Linked Open Data, covering different aspects of overlapping domains. This is typically the case of agronomy and related fields, where several LOD datasets describing different points of view on scientific classifications have been published. This opens emerging opportunities in the field, providing to practitioners new knowledge sources. However, without help, querying the different datasets is a time-consuming task for LOD users as they need to know the ontologies describing the data of each of them.
Rewriting queries can be automated with the help of ontology alignments. This paper presents a query rewriting approach that relies on complex alignments. This kind of alignment, opposite to simple ones, better deals with ontology modelling heterogeneities. We evaluate our approach on a scenario of query rewriting on agronomic information needs across four different datasets: AgronomicTaxon, AGROVOC, DBpedia, and TAXREF-LD.
Keywords: query rewriting; complex alignments; agronomic sources; linked open
Design of an ontology for detecting the social influence on non-communicable diseases risk factors
by Henrique Vianna, Jorge Barbosa, João Gluz, Renan Santos
Abstract: Non-communicable diseases are one of the greatest challenges of the twenty-first century. These diseases are caused by habits such as poor diets, lack of physical activity or smoking. Besides, social networks can play an important role in the spreading of such diseases as they regulate access to resources and opportunities to their members, and some studies have already correlated the influence of social relations in weight gain, feeling of happiness and in the decision of individuals to quit smoking. This paper presents the design of an ontology for detecting the social influence on the spreading of non-communicable diseases risk factors following Gruniger and Fox's methodology. Its motivation scenario focuses on the recommendation of beneficial connections to social network members. UML was used to represent domain and range of object properties, data properties, and subsumption, while the Manchester syntax was used to demonstrate equivalences. To test the ontology a small social network was created using axioms from the ontology in PROWLOG and defining the conditions necessary to the ontology, suggesting new connections in order that a node obtains a lower likelihood of obesity.
Keywords: ontology; chronic disease; ubiquitous computing.
A first-order logic expression of the CIDOC Conceptual Reference Model
by Carlo Meghini, Martin Doerr
Abstract: The CIDOC Conceptual Reference Model (CRM) is a well-known conceptual modelling language for documenting cultural heritage artifacts, with a special attention to museum objects. CRM is an ISO standard since 2006 (ISO21127:2006) and renewed 2014 (ISO21127:2014). The CRM is specified in a semantic data modelling style and relies on consolidated notions for the representation of knowledge such as classes, properties, Is A hierachies, domain and range constraints and cardinality restrictions. However, the CRM still lacks a formal specification of its semantic and inferential apparatus. This lack makes it difficult to clearly define fundamental operations on a CRM knowledge base, such as querying or consistency checking, while preventing any investigation on the computational properties of the language. This paper provides such an apparatus by expressing the CRM as a first-order theory. It then provides a reduction of the theory to a datalog program, and shows how the program can be used to effectively query a knowledge base taking into account the logical consequences of the represented knowledge.
Keywords: CIDOC CRM; ontology; metadata; logic.
Specification of semantic information of Arabic provisions
by Nasria Bouhyaoui, Fatima Zohra Laallam, Ismaïl Biskri
Abstract: Legal texts play an essential role in an organisation, be it public or private, where each actor must be aware of, and comply with, regulations. However, because of the difficulties of the legal domain, the actors prefer to rely on the expert rather than resorting to search for the regulation in a collection of documents. In this paper, we use a rule-based approach based on the contextual exploration method for the semantic annotation of Algerian legal texts written in Arabic language. We are interested in the specification of the semantic information of the three provision types, obligation, permission and prohibition, and the arguments' role and action. The preliminary experiment presents promising results for the specification of provision types.
Keywords: semantic annotation; law text; legal text; legal document; Arabic language; provision; rule-based; contextual exploration; linguistic approach.
SMART-ASD, model and ontology definition. A technology recommendation system for people with autism and/or intellectual disabilities
by Javier Sevilla, Javier J. Samper, Gerardo Herrera, Marcos Fernandez
Abstract: There are many studies that examine the use of mobile device solutions, with the adequate human intervention, to improve the skills of people with autism spectrum disorder (ASD). There are lot of apps that could be useful for people with ASD, but it is very difficult to choose the adequate technology help for them. The main goal of the SMART-ASD project is to help in the selection process of suitable technology and all the related accessories. In this project, all the users' data are maintained into an ontology. This ontology also includes information about devices, apps, protection systems and parents' and practitioners' preferences. The system develops a hybrid recommendation system that guides parents and professionals in the selection of suitable technology. In this paper, we explain the SMART-ASD model and its representation through an ontology, trying to reuse it from related projects.
Keywords: autism; ontology; mobile devices; recommendation system.
ANNETT-O: an ontology for describing artificial neural network evaluation, topology and training
by Iraklis Klampanos, Athanasios Davvetas, Antonis Koukourikos, Vangelis Karkaletsis
Abstract: Deep learning models, while effective and versatile, are becoming increasingly complex, often including multiple overlapping networks of arbitrary depths, multiple objectives and non-intuitive training methodologies. This makes it increasingly difficult for researchers and practitioners to design, train and understand them. In this paper we present ANNETT-O, a much-needed, generic and computer-actionable vocabulary for researchers and practitioners to describe their deep learning configurations, training procedures and experiments. The proposed ontology focuses on topological, training and evaluation aspects of complex deep neural configurations, while keeping peripheral entities more succinct. Knowledge bases implementing ANNETT-O can support a wide variety of queries, providing relevant insights to users. In addition to a detailed description of the ontology, we demonstrate its suitability to the task via a number of hypothetical use-cases of increasing complexity.rn
Keywords: ontologies; deep learning; artificial intelligence; semantic web; schemas; OWL; algorithm conceptsrn.