Collaborative Ontology Development Research Articles

A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development

Ontologies can represent technological enablers for knowledge elicitation and management in different kinds of organizations, especially with the exponential growth of sources and types of data fostered by digital transformation. However, their adoption in business applications is still limited, with existing Ontology Engineering Methodologies (OEMs) lacking adequate support during knowledge elicitation, authoring and reuse phases. This paper introduces a novel agile ontology engineering methodology (AgiSCOnt) to support ontologists (especially novice ones) in ontology development workflow, fostering collaboration with domain experts in an iterative, flexible and customizable approach. AgiSCOnt combines macro-level instructions with micro-level guidance, leveraging existing techniques and a management framework to help novice ontologists throughout the whole ontology engineering process. The methodology is compared to existing OEMs and assessed with three other agile methodologies (UPONLite, SAMOD, and RapidOWL). The evaluation is conducted with a sample of novice ontologists in a learning environment on Industry 4.0 technologies. Both the development process with a methodology from a user perspective and the quality of the developed ontologies were considered in the evaluation. Preliminary results show that AgiSCOnt effectively supports authoring and reuse, with developed ontologies of good quality. It is perceived as clear and simple, while being flexible and adaptable enough, thus supporting knowledge management and sharing in industrial organizations through the documentation of the ontologies.

Teachers’ Ontology-based Reasoning for Assessment in Student-centered Learning Environments

ABSTRACT We present an exploratory study on the use of ontologies for student assessment during a focus group with teachers in student-centred learning environments. The work is framed by a theoretical argument about coherence between instructional values and assessment systems, and how this may be achieved through a “community of judgment” with teachers at the centre. The purpose of the study was to understand the process and perceived usefulness of collaborative ontology development, at a narrative and conceptual level without grades or detailed probabilistic relationships. Findings of two kinds are discussed. First, we identified a set of framework-building moves used by teachers during ontology-based reasoning. Second, we present evidence that participants perceived the ontology development process to be useful and empowering in sharpening their ability to communicate nuanced assessment arguments.

Collaborative Ontology Development and its Use for Video Annotation in Elderly Care Domain

Collaborative Ontology Development and its Use for Video Annotation in Elderly Care Domain

Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective.

Summary Objectives : There exists a communication gap between the biomedical informatics community on one side and the computer science/artificial intelligence community on the other side regarding the meaning of the terms “semantic integration" and “knowledge representation“. This gap leads to approaches that attempt to provide one-to-one mappings between data elements and biomedical ontologies. Our aim is to clarify the representational differences between traditional data management and semantic-web-based data management by providing use cases of clinical data and clinical research data re-representation. We discuss how and why one-to-one mappings limit the advantages of using Semantic Web Technologies (SWTs). Methods : We employ commonly used SWTs, such as Resource Description Framework (RDF) and Ontology Web Language (OWL). We reuse pre-existing ontologies and ensure shared ontological commitment by selecting ontologies from a framework that fosters community-driven collaborative ontology development for biomedicine following the same set of principles. Results : We demonstrate the results of providing SWT-compliant re-representation of data elements from two independent projects managing clinical data and clinical research data. Our results show how one-to-one mappings would hinder the exploitation of the advantages provided by using SWT. Conclusions : We conclude that SWT-compliant re-representation is an indispensable step, if using the full potential of SWT is the goal. Rather than providing one-to-one mappings, developers should provide documentation that links data elements to graph structures to specify the re-representation.

UOSM: user-oriented semi-automatic method of constructing domain ontology

Based on the analysis of the existing main ontology construction methods and tools, we propose a user-oriented method of semi-automatic domain ontology construction. The method builds a descriptor set according to the user's requirements, and establishes a hierarchy structure based on it. Users can construct ontologies by using this method without the participation of experts. Additionally, the method has advantages for expansion and the collaborative development of ontologies.

UOSM: user-oriented semi-automatic method of constructing domain ontology

Based on the analysis of the existing main ontology construction methods and tools, we propose a user-oriented method of semi-automatic domain ontology construction. The method builds a descriptor set according to the user's requirements, and establishes a hierarchy structure based on it. Users can construct ontologies by using this method without the participation of experts. Additionally, the method has advantages for expansion and the collaborative development of ontologies.

Collaborative Ontology Development Approach for Multidisciplinary Knowledge: A Scenario-Based Knowledge Construction System in Life Cycle Assessment

Collaborative Ontology Development Approach for Multidisciplinary Knowledge: A Scenario-Based Knowledge Construction System in Life Cycle Assessment

The interplay of knowledge engineering and cognitive psychology: learning ontologies creating

The paper tries to marry cognitive issues of knowledge engineering and knowledge management in order to provide a new methodology for initial knowledge structuring. Ontology was chosen as the contemporary most comprehensive knowledge representation and codification model. Our approach uses participatory action research project in which some hypotheses about the relations between the cognitive style and ontology development are suggested. The methodology used simple, affordable technologies such as pen-and-pencil techniques for visual structuring experiments. The paper is aimed to integrate cognitive style individual features of knowledge analysts into the specifics of ontology design. It was found that personal peculiarities of cognitive style affect the topology and quality of knowledge structures. These findings provide some implications for collaborative ontology design and development. The knowledge structuring issues derived in this project can be used by managers and practitioners to address knowledge work and organisational learning.

Collaborative Ontology Development for the Geosciences

AbstractOntology‐based information publishing, retrieval, reuse, and integration have become popular research topics to address the challenges involved in exchanging data between heterogeneous sources. However, in most cases ontologies are still developed in a centralized top‐down manner by a few knowledge engineers. Consequently, the role that developers play in conceptualizing a domain such as the geosciences is disproportional compared with the role of domain experts and especially potential end‐users. These and other drawbacks have stimulated the creation of new methodologies focusing around collaboration. Based on a review of existing approaches, this article presents a two‐step methodology and implementation to foster collaborative ontology engineering in the geosciences. Our approach consists of the development of a minimalistic core ontology acting as a catalyst and the creation of a virtual collaborative development cycle. Both methodology and prototypical implementation have been tested in the context of the EU‐funded ForeStClim project which addresses environmental protection with respect to forests and climate change.

Levels of presenting ontologies, languages, mathematical models, and ontology web-server project in Web 2.0

This paper presents an ontology web-server project in Web 2.0 that allows the collaborative development of ontologies. The levels of presenting ontologies and mathematical models underlying these presentations are discussed. The CASL language (Common Algebraic Specification Language) is reviewed.

Semantic Support for Educational IT Services

Technology enhanced learning is one of the intensively researched domains, because it promises interesting contribution to modern educational processes at various levels, in particular in higher education. This paper presents our approach to design and implementation of semantic structures that are capable to support selected educational processes, e.g. in mathematical and computer science disciplines. The methodology for collaborative ontology development, applied on the analyzed domain of eleven courses, is proposed as a generic approach that can be potentially reused and adapted to create semantic models of other domains (courses, disciplines) for semantically supported technology enhanced learning applications. The resulting structure of developed ontologies is presented as a basis for constructing semantically enhanced electronic services that can be further orchestrated and integrated into complex educational processes. This approach may provide powerful means to educators at universities, namely for (semi- )automated preparation, running, and maintenance of their courses. Added semantics, by enabling an integration of learning services into specified educational processes, is capable to minimize the efforts of educators when preparing and running a new lecture or course, as well as to effectively analyze the whole process and the students' performance.

A holistic approach to collaborative ontology development based on change management

This paper describes our methodological and technological approach for collaborative ontology development in inter-organizational settings. It is based on the formalization of the collaborative ontology development process by means of an explicit editorial workflow, which coordinates proposals for changes among ontology editors in a flexible manner. This approach is supported by new models, methods and strategies for ontology change management in distributed environments: we propose a new form of ontology change representation, organized in layers so as to provide as much independence as possible from the underlying ontology languages, together with methods and strategies for their manipulation, version management, capture, storage and maintenance, some of which are based on existing proposals in the state of the art. Moreover, we propose a set of change propagation strategies that allow keeping distributed copies of the same ontology synchronized. Finally, we illustrate and evaluate our approach with a test case in the fishery domain from the United Nations Food and Agriculture Organisation (FAO). The preliminary results obtained from our evaluation suggest positive indication on the practical value and usability of the work here presented.

A Holistic Approach to Collaborative Ontology Development Based on Change Management

This paper describes our methodological and technological approach for collaborative ontology development in inter-organizational settings. It is based on the formalization of the collaborative ontology development process by means of an explicit editorial workflow, which coordinates proposals for changes among ontology editors in a flexible manner. This approach is supported by new models, methods and strategies for ontology change management in distributed environments: we propose a new form of ontology change representation, organised in layers so as to provide as much independence as possible from the underlying ontology languages, together with methods and strategies for their manipulation, version management, capture, storage and maintenance, some of which are based on existing proposals in the state of the art. Moreover, we propose a set of change propagation strategies that allow keeping distributed copies of the same ontology synchronized. Finally, we illustrate and evaluate our approach with a test case in the fishery domain from the United Nations Food and Agriculture Organisation (FAO). The preliminary results obtained from our evaluation suggest positive indication on the practical value and usability of the work here presented.

A gross anatomy ontology for hymenoptera.

Hymenoptera is an extraordinarily diverse lineage, both in terms of species numbers and morphotypes, that includes sawflies, bees, wasps, and ants. These organisms serve critical roles as herbivores, predators, parasitoids, and pollinators, with several species functioning as models for agricultural, behavioral, and genomic research. The collective anatomical knowledge of these insects, however, has been described or referred to by labels derived from numerous, partially overlapping lexicons. The resulting corpus of information—millions of statements about hymenopteran phenotypes—remains inaccessible due to language discrepancies. The Hymenoptera Anatomy Ontology (HAO) was developed to surmount this challenge and to aid future communication related to hymenopteran anatomy. The HAO was built using newly developed interfaces within mx, a Web-based, open source software package, that enables collaborators to simultaneously contribute to an ontology. Over twenty people contributed to the development of this ontology by adding terms, genus differentia, references, images, relationships, and annotations. The database interface returns an Open Biomedical Ontology (OBO) formatted version of the ontology and includes mechanisms for extracting candidate data and for publishing a searchable ontology to the Web. The application tools are subject-agnostic and may be used by others initiating and developing ontologies. The present core HAO data constitute 2,111 concepts, 6,977 terms (labels for concepts), 3,152 relations, 4,361 sensus (links between terms, concepts, and references) and over 6,000 text and graphical annotations. The HAO is rooted with the Common Anatomy Reference Ontology (CARO), in order to facilitate interoperability with and future alignment to other anatomy ontologies, and is available through the OBO Foundry ontology repository and BioPortal. The HAO provides a foundation through which connections between genomic, evolutionary developmental biology, phylogenetic, taxonomic, and morphological research can be actualized. Inherent mechanisms for feedback and content delivery demonstrate the effectiveness of remote, collaborative ontology development and facilitate future refinement of the HAO.

Cognitive ontologies for neuropsychiatric phenomics research

Now that genome-wide association studies (GWAS) are dominating the landscape of genetic research on neuropsychiatric syndromes, investigators are being faced with complexity on an unprecedented scale. It is now clear that phenomics, the systematic study of phenotypes on a genome-wide scale, comprises a rate-limiting step on the road to genomic discovery. To gain traction on the myriad paths leading from genomic variation to syndromal manifestations, informatics strategies must be deployed to navigate increasingly broad domains of knowledge and help researchers find the most important signals. The success of the Gene Ontology project suggests the potential benefits of developing schemata to represent higher levels of phenotypic expression. Challenges in cognitive ontology development include the lack of formal definitions of key concepts and relations among entities, the inconsistent use of terminology across investigators and time, and the fact that relations among cognitive concepts are not likely to be well represented by simple hierarchical “tree” structures. Because cognitive concept labels are labile, there is a need to represent empirical findings at the cognitive test indicator level. This level of description has greater consistency, and benefits from operational definitions of its concepts and relations to quantitative data. Considering cognitive test indicators as the foundation of cognitive ontologies carries several implications, including the likely utility of cognitive task taxonomies. The concept of cognitive “test speciation” is introduced to mark the evolution of paradigms sufficiently unique that their results cannot be “mated” productively with others in meta-analysis. Several projects have been initiated to develop cognitive ontologies at the Consortium for Neuropsychiatric Phenomics (www.phenomics.ucla.edu), in the hope that these ultimately will enable more effective collaboration, and facilitate connections of information about cognitive phenotypes to other levels of biological knowledge. Several free web applications are available already to support examination and visualisation of cognitive concepts in the literature (PubGraph, PubAtlas, PubBrain) and to aid collaborative development of cognitive ontologies (Phenowiki and the Cognitive Atlas). It is hoped that these tools will help formalise inference about cognitive concepts in behavioural and neuroimaging studies, and facilitate discovery of the genetic bases of both healthy cognition and cognitive disorders.

Grid technology for collaborative ontology development

AbstractIn contrast with the centrally-organised curation of the Gene Ontology, many biological ontologies are developed by loosely-organised groups who develop their ontology remotely. These groups tend to be formed from scientists and bio-informaticians from research groups with a common interest, who want to create a resource that will be useful to the community, rather than being formally mandated. Until recently, technological support for bio-ontology development relied on stand-alone editors running on users’ desk- tops for creating new ontology versions (e.g. OBO-Edit, COBrA and Protégé) and on private email, email lists and perhaps Wikis for the distribution of ontology files and discussions. Clearly, much better use could be made of the storage, versioning and visualisation techniques being developed by the database and e- Science communities. BioSphere is an online ontology editor supporting multiple users and is underpinned by a server that stores versions (in OWL-XML) and provides a discussion portal.

Grid technology for collaborative ontology development

Grid technology for collaborative ontology development

An Ontology Abstract Machine

� Abstract—As more people from non-technical backgrounds are becoming directly involved with large-scale ontology development, the focal point of ontology research has shifted from the more theoretical ontology issues to problems associated with the actual use of ontologies in real-world, large-scale collaborative applications. Recently the National Science Foundation funded a large collaborative ontology development project for which a new formal ontology model, the Ontology Abstract Machine (OAM), was developed to satisfy some unique functional and data representation requirements. This paper introduces the OAM model and the related algorithms that enable maintenance of an ontology that supports node-based user access. The successful software implementation of the OAM model and its subsequent acceptance by a large research community proves its validity and its real-world application value.