Ontology Design Research Articles

A document-centric approach for developing the tolAPC ontology

BackgroundThere are many challenges associated with ontology building, as the process often touches on many different subject areas; it needs knowledge of the problem domain, an understanding of the ontology formalism, software in use and, sometimes, an understanding of the philosophical background. In practice, it is very rare that an ontology can be completed by a single person, as they are unlikely to combine all of these skills. So people with these skills must collaborate. One solution to this is to use face-to-face meetings, but these can be expensive and time-consuming for teams that are not co-located. Remote collaboration is possible, of course, but one difficulty here is that domain specialists use a wide-variety of different “formalisms” to represent and share their data – by the far most common, however, is the “office file” either in the form of a word-processor document or a spreadsheet.Here we describe the development of an ontology of immunological cell types; this was initially developed by domain specialists using an Excel spreadsheet for collaboration. We have transformed this spreadsheet into an ontology using highly-programmatic and pattern-driven ontology development. Critically, the spreadsheet remains part of the source for the ontology; the domain specialists are free to update it, and changes will percolate to the end ontology.ResultsWe have developed a new ontology describing immunological cell lines built by instantiating ontology design patterns written programmatically, using values from a spreadsheet catalogue.ConclusionsThis method employs a spreadsheet that was developed by domain experts. The spreadsheet is unconstrained in its usage and can be freely updated resulting in a new ontology. This provides a general methodology for ontology development using data generated by domain specialists.

Validating EHR clinical models using ontology patterns

Clinical models are artefacts that specify how information is structured in electronic health records (EHRs). However, the makeup of clinical models is not guided by any formal constraint beyond a semantically vague information model. We address this gap by advocating ontology design patterns as a mechanism that makes the semantics of clinical models explicit.This paper demonstrates how ontology design patterns can validate existing clinical models using SHACL. Based on the Clinical Information Modelling Initiative (CIMI), we show how ontology patterns detect both modeling and terminology binding errors in CIMI models.SHACL, a W3C constraint language for the validation of RDF graphs, builds on the concept of “Shape”, a description of data in terms of expected cardinalities, datatypes and other restrictions. SHACL, as opposed to OWL, subscribes to the Closed World Assumption (CWA) and is therefore more suitable for the validation of clinical models.We have demonstrated the feasibility of the approach by manually describing the correspondences between six CIMI clinical models represented in RDF and two SHACL ontology design patterns. Using a Java-based SHACL implementation, we found at least eleven modeling and binding errors within these CIMI models. This demonstrates the usefulness of ontology design patterns not only as a modeling tool but also as a tool for validation.

Ontology design patterns and semantic abstractions in ontology integration

Ontology design patterns and semantic abstractions in ontology integration

An ontology for numerical design of experiments processes

Numerical Designs of Experiments (NDoE) are used in a product development process to optimize the product. A NDoE may combine a costly numerical model and numerous experiments. The NDoE process consequently becomes very expensive. However, some methods and algorithms were developed to shorten the NDoE process, as sensitivity analysis, surrogate modelling and adaptive DoE. Because of their complexity, advanced expert knowledge or a long preparation step is required to optimally choose and configure all of these methods, in order to run the most efficient NDoE process.To answer this issue, a knowledge management approach is proposed in this paper. It capitalizes and reuses knowledge about NDoE process. This solution is proposed because of the lack in term of models and standardized processes for this specific NDoE application. An ontology was developed to manage, share and reuse knowledge and enable queries for information retrieval in a database. The database lists every NDoE processes executed. Then, the knowledge is analysed by a decision-support system to help designers to choose the best configuration.

Towards Building a Semantic Repository of Bioinformatics Resources

The paper presents a work in progress directed to the creation of a semantic digital repository of scholarly resources in the area of bioinformatics. A special attention has been paid to the design of a lightweight subject ontology that will be used for automated conceptual annotation of the dynamically entering new materials and as a knowledge source for intelligent search over the repository. Some issues concerning the implementation of the repository and a suitable tool for search and document retrieval over its resources are discussed as well.

Standard International Trade Classification

Trade classifications are a necessary prerequisite for the compilation of trade statistics, and they should – beyond that – be regarded as a valuable base for the definition of shared controlled vocabularies for linked business data that deal with import, export etc. The Standard International Trade Classification (SITC) provided by the UN Statistics Division is a widely used classification mostly applied for scientific and analytical purposes. SITC – as most other trade classifications – is available today only in text or spreadsheet formats. These formats reveal the inner hierarchical structure of SITC to the human reader, because SITC trade codes are built according to the decimal classification scheme, but unfortunately, SITC’s inner structure is opaque to computer applications in text and spreadsheet formats. The paper discusses an approach to set up an OWL-2 ontology for SITC that states subsumption relations between classes of goods. This kind of semantic underpinning of SITC is suited to ease both checking and extending SITC and to derive from it a shared controlled vocabulary for business linked data. Some problems of today’s SITC (among them missing inner nodes of the trade code hierarchy) are carefully discussed, and the paper motivates several decisions that were taken for ontology design. Finally, the study introduces the semantic reasoner as a tool for the (at least partial) automatic derivation of structural information for SITC from the trade code building rule. The paper reports on reasoner runtimes observed for different versions of the SITC ontology and for different versions of the Pellet reasoner.

A Structural Analysis of topic ontologies

DMOZ is the largest human-edited topic ontology available on the Web. This article studies the structural properties of the DMOZ graph. A number of global and local properties of this graph and the subgraphs resulting from isolating edges of different types are examined by means of metrics commonly used in complex network analysis. In particular, we investigate the presence of various features that characterize small-world networks. This analysis is complemented by examining other characteristics of the graphs such as connectivity and centrality measures. The connectivity and centrality patterns are further studied by means of visualizations of the graphs’ k-core decomposition and a selection of strongly connected components. Several non-trivial regularities that are also encountered in other artificial and natural complex networks provide a general picture of this large human-edited topic ontology. This analysis is of major pragmatic interest as it allows a better understanding of notions such as navigability among topics, hierarchical structure and topic cohesiveness, which are of great importance in the design of topic ontologies.

Enhancing semantic consistency in anti-fraud rule-based expert systems

In this study, an ontology-driven approach is proposed for semantic conflict detection and classification in rule-based expert systems. It focuses on the critical case of anti-fraud rule repositories for the inspection of Card Not Present (CNP) transactions in e-commerce environments. The main motivation is to examine and curate anti-fraud rule datasets to avoid semantic conflicts that could lead the underpinning expert system to incorrectly perform, e. g., by accepting fraudulent transactions and/or by discarding harmless ones. The proposed approach is based on Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) technologies to develop an anti-fraud rule ontology and reasoning tasks, respectively. The three main contributions of this work are: first, the creation of a conceptual knowledge model for describing anti-fraud rules and their relationships; second, the development of semantic rules as conflict-resolution methods for anti-fraud expert systems; third, experimental facts are gathered to evaluate and validate the proposed model. A real-world use case in the e-commerce (e-Tourism) industry is used to explain the ontological knowledge design and its use. The experiments show that ontological approaches can effectively discover and classify conflicts in rule-based expert systems in the field of anti-fraud applications. The proposal is also applicable to other domains where knowledge rule bases are involved.

Semantically Defining Populations for 'Omics Research

The study of populations is central to ‘omics research, whether sequencing environmental samples, controlling for population structure when looking for genetic variation within a species, or studying the evolution of large clades. Researchers use different operational definitions of populations and communities, via the highly varied creation of operational taxonomic units (OTUs) and, in some cases, use of unclustered sequences. The use of different methods, even within one study type (Swarm, UCLUST, CD HIT, etc.), creates very different OTUs, possibly affecting interpretation and leading to questionable reproducibility. The Population and Community Ontology (PCO) offers the semantics to clarify exactly which collection of organisms (i.e., ecological community or population) was used in an investigation. When combined with methods for standardizing observational data from the BioCollections Ontology (BCO), protocol classes from the Ontology for Biomedical investigations (OBI), and characterization of environments from the Environment Ontology (ENVO), PCO can fully describe the methods used to derive organismal or species-based (i.e. taxonomic) OTUs used for biodiversity analysis and monitoring. PCO is not well suited to describe “OTUs” based on sequence variants that may or may not map to population or individual level variation (e.g., output of some clustering algorithms). In this case, the Sequence Ontology (SO) may be more appropriate. This presentation will describe the key ontology design patterns used in the PCO and provide examples of how and when PCO and related ontologies should be used in omics research, with a focus on environmental/metagenomic sequencing applications.

A semantic model for axiomatic systems design

Design of large-scale engineering systems such as an automobile, satellite, or airplane is a process to satisfy requirements by making various decisions. Design axioms provide system designers with a theoretical background to make right decisions. However, the axiomatic systems design is still hard to be implemented in the real word due to its informal representation for both the human and machine, and few researches focus on formalizing concepts of this process. In order to define axiomatic systems design models to be both user-understandable and machine-readable, this paper combines axiomatic design process with the Semantic Web technology and proposes an axiomatic design semantic representation model, called axiomatic design ontology, which organizes customers’ requirements, functional requirements, design parameters, and design solutions. The class of concepts elements and their semantic relationships are defined by the Web Ontology Language (OWL2). Rules for identifying functional couplings (the Independence Axiom) and selecting the optimal design solution (the Information Axiom) are formally represented and encoded with the Semantic Web Rule Language, which enhances the reasoning capability of the axiomatic design ontology. A framework for capturing systems design semantic information based on the axiomatic design ontology, and aligning it with domain-specific ontologies according to the semantic mapping approach has been developed, by which elaborated design information is captured and shared. Finally, a case study of systems design of a satellite solar wing subsystem is given to demonstrate the proposed axiomatic design ontology-based systems design approach.

Automatic Ontology Construction Using Text Corpora and Ontology Design Patterns (ODPs) in Alzheimer’s Disease

An ontology is defined as an explicit specification of a conceptualization, which is an important tool for modeling, sharing and reuse of domain knowledge. However, ontology construction by hand is a complex and a time consuming task. This research presents a fully automatic method to build bilingual domain ontology from text corpora and ontology design patterns (ODPs) in Alzheimer’s disease. This method combines two approaches: ontology learning from texts and matching with ODPs. It consists of six steps: (i) Term & relation extraction (ii) Matching with Alzheimer glossary (iii) Matching with ontology design patterns (iv) Score computation similarity term & relation with ODPs (v) Ontology building (vi) Ontology evaluation. The result of ontology composed of 381 terms and 184 relations with 200 new terms and 42 new relations were added. Fully automatic ontology construction has higher complexity, shorter time and reduces role of the expert knowledge to evaluate ontology than manual ontology construction. This proposed method is sufficiently flexible to be applied to other domains.

Solutions for system analysis and information support of the various activities in the Arctic

Comprehensive use of data and knowledge obtained within different disciplines is necessary for the scientific substantiation of activities in the Arctic zone and for a system analysis of the possible consequences of this activity. Information resources created so far allow the access to a variety of data on the Arctic. The authors propose the solution for task of data consistency ensuring in the field of combined presentation and use of data and knowledge of interdisciplinary research. The proposed solution is based on the joint use of relational database and ontology. The developed structure and mechanisms of the database maintenance provide a uniform representation of the information about results of the researches executed in the framework of various disciplines. The ontology is a high-level global schema of the information system and it provides a dictionary that is used to formulate a database query in terms of a subject domain. In this work, ontology is implemented as a system of small fragments - ontology design patterns. The patterns use makes it possible to perform efficient preliminary database indexing, which ensures faster execution of user queries.

Formal ontology and CAD integration with macro parametric approach

ABSTRACTThis paper discusses an ontological integration framework in the context of mereotopological formal ontology and CAD systems. Based on a comprehensive literature review of current design knowledge management and formal ontology research works, the authors propose the integration framework that can incorporate design knowledge with CAD systems. The primary role of mereotopology in this research work is the formal representation of design knowledge for the 3D solid assembly models. Most of the existing research works about design ontology present an abstract form and often require significant additional efforts to be integrated into CAD systems. Thus, this work introduces a formal ontology for CAD (OCAD) and macro-parametric approach as a practical way to integrate design knowledge with CAD systems. For the implementation, Protege, SPARQL, and commercial CAD system are employed. We also propose the enhancement of the developed framework for the future use to aid dynamic modeling.

An Ontology Design Pattern and its use case for modeling material transformation

An Ontology Design Pattern and its use case for modeling material transformation

Ontology for design of active fall protection systems

Abstract This paper aims to develop an ontology (AFPS-Onto) which formalizes the knowledge of active fall protection system (AFPS) design, with attempt to facilitate knowledge sharing and reuse. METHONTOLOGY was adopted as a method to build the AFPS-Onto. The AFPS-Onto consists of nine core concepts: hazard, actor, task, ifc building element, construction method, constraint, safety resource, hazard control measure, and residual risk. The concepts, relations, attributes, and axioms were coded using Protege. The ontology was evaluated through automated consistency checking, criteria-based and task-based evaluation. The AFPS-Onto fills the knowledge gap by providing a formal and shared vocabulary for the domain of AFPS design. This can promote knowledge reuse and sharing among professional engineers. In addition, the ontology can be used to develop knowledge-based systems to help design effective AFPS. Future effort can be made to develop ontologies of other control measures against fall from heights and combine them into a fall from heights ontology (FFH-Onto).

Use of technologically and topologically related surfaces (TTRS) geometrical theory for mechatronic design ontology

This paper presents the MBSE challenges related to the conceptual design of mechatronic systems and especially the need to ensure geometrical knowledge consistency. To tackle this issue, we propose to define an ontology based on the TTRS (Technologically and Topologically Related Surfaces) geometrical modeling. We implement it in the Protege environment and validate it through the modeling process of an Electric Power Train, including many additional geometrical issues related to mechatronic system design, such as physical integration and the related compactness metric and the thermal modeling for multi-physical couplings. Geometrical knowledge consistency has been ensured through a model transformation between SysML and FreeCAD, using Python.

Socio-critical research on teaching physical education and physical education teacher education

The purpose of this study is to systematically review the socio-critical research on teaching physical education (PE) and PE teacher education (PETE) between 1999 and 2014. The procedure followed a four-phase approach: (a) searching publications through four international databases; (b) meeting inclusion criteria; (c) refining selection to identify specifically research-based papers; and (d) expert searching based on the research team’s knowledge. The selection process yielded 23 articles mainly from Australia, New Zealand, the USA and Spain. Most of the research was authored collaboratively by male and female authors affiliated to universities. A lack of authorship shared with participant students, teachers or student teachers was observed. Qualitative approaches were the predominant methodology used in the selected studies. An inductive content analysis identified five major themes: evaluations in secondary school; evaluations in higher education; provocative studies; studies on assessment; and studies on participants’ experiences and views. Teaching and curriculum problems and difficulties, new ways of approaching them and potential solutions to moral struggles in teaching were analysed within these themes. Most of the socio-critical research reviewed involved both a postmodern ontology and innovative research designs to investigate the new and complex world of PE and PETE. This review exhibits the reduced impact on social change and the difficulties in developing socio-critical research and enacting critical pedagogy. However, the findings of our study preserve the momentum of socio-critical research that fights to keep its place in the field of teaching PE and PETE.

An approach to translating OCL invariants into OWL 2 DL axioms for checking inconsistency

Checking the design specification for contradictions at the early phase of the software development process is crucial to ensure that the design is implementable. However, the high expressivity of OCL makes manual inconsistency checking a difficult task. In addition, the developers cannot detect these problems by OCL itself due to its lack of automated reasoning support. We investigate an approach to translating OCL invariants into OWL 2 DL axioms. We do this where the OCL expression contained in an invariant is converted to the corresponding OWL 2 DL class expression in a compositional way. Our approach covers the OCL expressions including four: PrimaryExp, RelationalExp, LogicalExp and IfExp types. Considering the distinction between the CWA and OWA, we achieve correct translation from RelationalExp using closure axiom. Also, we employ an ontology design pattern to overcome the limitations of OWL 2 DL expressivity when translating IfExp. Then inconsistency checking is done through description logic reasoning by the OWL 2 DL high-performance reasoner. We construct an inductive proof to establish the correctness of our translation approach. Moreover, we evaluate our approach using the implemented TUCO tool prototype.

Ontology-Driven Generation of Radiation Protection Procedures

In this article, we present the principle and suitable methodology for the design of a medical ontology that highlights the radiological and dosimetric knowledge, applied in diagnostic radiology and radiation-therapy. Our ontology, which we named «Onto.Rap», is the subject of radiation protection in medical and radiology centers by providing a standardized regulatory oversight. Thanks to its added values of knowledge-sharing, reuse and the ease of maintenance, this ontology tends to solve many problems. Of which we name the confusion between radiological procedures a practitioner might face while performing a patient radiological exam. Adding to it, the difficulties they might have in interpreting applicable patient radioprotection standards. Here, the ontology, thanks to its concepts simplification and expressiveness capabilities, can ensure an efficient classification of radiological procedures. It also provides an explicit representation of the relations between the different components of the studied concept. In fact, an ontology based-radioprotection expert system, when used in radiological center, could implement systematic radioprotection best practices during patient exam and a regulatory compliance service auditing afterwards.

Towards a Common Framework for the Identification of Landforms on Terrain Models

A landform is a physical feature of the terrain with its own recognisable shape. Its definition is often qualitative and inherently vague. Hence, landforms are difficult to formalise in a logical model that can be implemented. We propose for that purpose a framework where these qualitative and vague definitions are transformed successively during different phases to yield an implementable data structure. Our main consideration is that landforms are characterised by salient elements as perceived by users. Hence, a common prototype based on an object-oriented approach is defined that shall apply to all landforms. This framework shall facilitate the definition of conceptual models for other landforms and relies on the use of ontology design patterns to express common elements and structures. The model is illustrated on examples from the literature, showing that existing works undertaken separately can be developed under a common framework.