Ontology selection: ontology evaluation on the real Semantic Web

The increasing number of ontologies on the Web and the appearance of large scale ontology repositories has brought the topic of ontology selection in the focus of the semantic web research agenda. Our view is that ontology evaluation is core to ontology selection and that, because ontology selection is performed in an open Web environment, it brings new challenges to ontology evaluation. Unfortunately, current research regards ontology selection and evaluation as two separate topics. Our goal in this paper is to explore how these two tasks relate. In particular, we are interested to get a better understanding of the ontology selection task and filter out the challenges that it brings to ontology evaluation. We discuss requirements posed by the open Web environment on ontology selection, we overview existing work on selection and point out future directions. Our major conclusion is that, even if selection methods still need further development, they have already brought novel approaches to ontology evaluatio

Methodology and ontology in microbiome research

Research on the human microbiome has gen- erated a staggering amount of sequence data, revealing variation in microbial diversity at the community, species (or phylotype), and genomic levels. In order to make this complexity more manageable and easier to interpret, new units—the metagenome, core microbiome, and entero- type—have been introduced in the scientific literature. Here, I argue that analytical tools and exploratory statisti- cal methods, coupled with a translational imperative, are the primary drivers of this new ontology. By reducing the dimensionality of variation in the human microbiome, these new units render it more tractable and easier to interpret, and hence serve an important heuristic role. Nonetheless, there are several reasons to be cautious about these new categories prematurely ‘‘hardening’’ into natural units: a lack of constraints on what can be sequenced metagenomically, freedom of choice in taxonomic level in defining a ‘‘core microbiome,’’ typological framing of some of the concepts, and possible reification of statistical constructs. Finally, lessons from the Human Genome Project have led to a translational imperative: a drive to derive results from the exploration of microbiome variation that can help to articulate the emerging paradigm of per- sonalized genomic medicine (PGM). There is a tension between the typologizing inherent in much of this research and the personal in PGM

Ontology learning for semantic web services

Semantic Web Services promise automatic service discovery and composition, relying heavily on domain ontology as a core component. With large Web Service repository, manual ontology development is proving a bottleneck (with associated expense and likely errors) to the realisation of a semantic Web of services. Providing the appropriate tools that assist in and automate ontology development is essential for a dynamic service vision to be realised. As a statement of research-in-progress, this paper proposes combining different ontology learning paradigms in Web Services domain, highlighting the need for further research that accommodates the variation in Web Service descriptive and operational sources. A research agenda is proposed that recognises this variation in artefacts as they are selected, pre-processed and analyzed by ontology learning techniques

Ontological Foundations for Geographic Information Science

We propose as a UCGIS research priority the topic of “Ontological Foundations for Geographic Information.” Under this umbrella we unify several interrelated research subfields, each of which deals with different perspectives on geospatial ontologies and their roles in geographic information science. While each of these subfields could be addressed separately, we believe it is important to address ontological research in a unitary, systematic fashion, embracing conceptual issues concerning what would be required to establish an exhaustive ontology of the geospatial domain, issues relating to the choice of appropriate methods for formalizing ontologies, and considerations regarding the design of ontology-driven information systems. This integrated approach is necessary, because there is a strong dependency between the methods used to specify an ontology, and the conceptual richness, robustness and tractability of the ontology itself. Likewise, information system implementations are needed as testbeds of the usefulness of every aspect of an exhaustive ontology of the geospatial domain. None of the current UCGIS research priorities provides such an integrative perspective, and therefore the topic of “Ontological Foundations for Geographic Information Science” is unique

Using Ontology Research in Semantic Web Applications

In the light of improving the World Wide Web, researchers are working towards the Semantic Web. Ontologies and ontology-based applications are its basic ingredients. Several ontological environments, categorizations and methodologies can be found in the literature. This paper shows how we have investigated the state of the art in these areas in an ontology building process that is the basis for an application developed at the later stage in an events organisation domain

Ontologies Change and Queries Break: Towards a Solution

Keeping track of ontology changes is becoming a critical issue for ontology-based applications. Updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of mapping ontology versions and keeping consistent with the instances. Very little work investigated controlling the impact on dependent applications/services; which is the aim of the system presented in this paper. The approach we propose is to make use of ontology change logs to analyse incoming RDQL queries and amend them as necessary. Revised queries can then be used to query the ontology and knowledge base as requested by the applications and services. We describe the design of our prototype system, and discuss related problems and future directions

Uberon: towards a comprehensive multi-species anatomy ontology

The lack of a single unified species-neutral ontology covering the anatomy of a variety of metazoans is a hindrance to translating model organism research to human health. We have developed an Uber-anatomy ontology to fill this need, filling the gap between the CARO upper-level ontology and species-specific anatomical ontologies

An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

The devices, experimental scaffolds, and biomaterials ontology (DEB): a tool for mapping, annotation, and analysis of biomaterials' data

The size and complexity of the biomaterials literature makes systematic data analysis an excruciating manual task. A practical solution is creating databases and information resources. Implant design and biomaterials research can greatly benefit from an open database for systematic data retrieval. Ontologies are pivotal to knowledge base creation, serving to represent and organize domain knowledge. To name but two examples, GO, the gene ontology, and CheBI, Chemical Entities of Biological Interest ontology and their associated databases are central resources to their respective research communities. The creation of the devices, experimental scaffolds, and biomaterials ontology (DEB), an open resource for organizing information about biomaterials, their design, manufacture, and biological testing, is described. It is developed using text analysis for identifying ontology terms from a biomaterials gold standard corpus, systematically curated to represent the domain's lexicon. Topics covered are validated by members of the biomaterials research community. The ontology may be used for searching terms, performing annotations for machine learning applications, standardized meta-data indexing, and other cross-disciplinary data exploitation. The input of the biomaterials community to this effort to create data-driven open-access research tools is encouraged and welcomed.Preprin

The Infectious Disease Ontology in the Age of COVID-19

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research