Resource Ontology Research Articles

TrhOnt: building an ontology to assist rehabilitation processes.

BackgroundOne of the current research efforts in the area of biomedicine is the representation of knowledge in a structured way so that reasoning can be performed on it. More precisely, in the field of physiotherapy, information such as the physiotherapy record of a patient or treatment protocols for specific disorders must be adequately modeled, because they play a relevant role in the management of the evolutionary recovery process of a patient. In this scenario, we introduce TrhOnt, an application ontology that can assist physiotherapists in the management of the patients’ evolution via reasoning supported by semantic technology.MethodsThe ontology was developed following the NeOn Methodology. It integrates knowledge from ontological (e.g. FMA ontology) and non-ontological resources (e.g. a database of movements, exercises and treatment protocols) as well as additional physiotherapy-related knowledge.ResultsWe demonstrate how the ontology fulfills the purpose of providing a reference model for the representation of the physiotherapy-related information that is needed for the whole physiotherapy treatment of patients, since they step for the first time into the physiotherapist’s office, until they are discharged. More specifically, we present the results for each of the intended uses of the ontology listed in the document that specifies its requirements, and show how TrhOnt can answer the competency questions defined within that document. Moreover, we detail the main steps of the process followed to build the TrhOnt ontology in order to facilitate its reproducibility in a similar context. Finally, we show an evaluation of the ontology from different perspectives.Conclusions TrhOnt has achieved the purpose of allowing for a reasoning process that changes over time according to the patient’s state and performance.

Nanoinformatics: Problems, methods, and technologies

This paper outlines the range of problems solved by nanoinformatics, which is a newly originated discipline that combines the methods and tools for the propagation of data on nanomaterials as well as the instruments and technologies based on them. The specific features determined by the interdisciplinary character and rapid evolution of this knowledge area are summarized for the data on the properties of nanosized objects. The most-popular resources (databases, classifiers, and ontologies) on the properties of nanomaterials are presented. Some topical disproportions, which have occurred in nanoinformatics due to the predominant attention to nanomedicine at the expense of the traditional application fields of nanotechnologies, such as electronics and energetics, are pointed out. The general nanomaterial terminology and classification standards, which form a basis for the design of new databases and ontologies, are considered in detail. The CODATA (Committee on Data for Science and Technology) international standard for the universal description of a nanomaterial is proposed for use as the most advanced and universal approach to the solution of problems in nanoinformatics.

CoreALMlib: An library translated from the Component Library

AbstractThis paper presents CoreALMlib, an $\mathscr{ALM}$ library of commonsense knowledge about dynamic domains. The library was obtained by translating part of the Component Library (CLib) into the modular action language $\mathscr{ALM}$. CLib consists of general reusable and composable commonsense concepts, selected based on a thorough study of ontological and lexical resources. Our translation targets CLibstates (i.e., fluents) and actions. The resulting $\mathscr{ALM}$ library contains the descriptions of 123 action classes grouped into 43 reusable modules that are organized into a hierarchy. It is made available online and of interest to researchers in the action language, answer-set programming, and natural language understanding communities. We believe that our translation has two main advantages over its CLib counterpart: (i) it specifies axioms about actions in a more elaboration tolerant and readable way, and (ii) it can be seamlessly integrated with ASP reasoning algorithms (e.g., for planning and postdiction). In contrast, axioms are described in CLib using STRIPS-like operators, and CLib's inference engine cannot handle planning nor postdiction.

The Non-existence of Ontological Categories: A defence of Lowe

Abstract This paper addresses the ontological status of the ontological categories as defended within E.J. Lowe’s four-category ontology (kinds, objects, properties/relations, and modes). I consider the arguments in Griffith (2015. “Do Ontological Categories Exist?” Metaphysica 16 (1):25–35) against Lowe’s claim that ontological categories do not exist, and argue that Griffith’s objections to Lowe do not work once we fully take advantage of ontological resources available within Lowe’s four-category ontology. I then argue that the claim that ontological categories do not exist has no undesirable consequences for Lowe’s brand of realism.

Emerging Trends in Reducing Semantic Gap towards Multimedia Access: A Comprehensive Survey

Objectives: The exponential growth of web has increased the volume of the documents. Data does not carry any meaning, but it should be interpreted efficiently for execution of query. Semantic web is combined with statistical and machine learning techniques to increase the efficiency of an information retrieval system. Semantic web supports reasoning of uncertain and vague knowledge for applications like multimedia processing, ubiquitous contexts, etc. Method: Resource Description Framework and Ontology Web Language are standard formats for sharing and integrating knowledge. This paper includes the recent trends in accessing the information in semantic web and reducing semantic gap. Findings: This paper provides an overview of contemporary challenges and open research issues in reducing the Semantic gap. Application/Improvement: Use of Description logics increases the efficiency of semantic retrieval.

Contending Geo-Logics: Energy Security, Resource Ontologies, and the Politics of Expert Knowledge in Estonia

ABSTRACTEngaging with nascent scholarly efforts to foreground the ‘geo’ of geopolitics, this article examines how certain low-quality geological substances are constituted as strategic, ‘unconventional’ fossil fuel resources, the exploitation of which is deemed indispensable for energy security reasons. Based on a detailed study of oil shale exploitation in Estonia, the paper specifically analyses the politics of knowledge that enable such carbon-intensive and energy-inefficient industries to perpetuate at the national level and, moreover, subvert the neoliberal imperatives of energy sector deregulation and decarbonisation arising from EU policies. This analysis leads to two key arguments. At one level, the Estonian case evidences and contextualises the growing recognition that ‘energy security’ represents a multifaceted and dynamic construct as it highlights, in particular, the contingency of expert knowledge in its conceptualisation and performance. What counts as energy security is in this case articulated via shifting and contested modes of knowledge-making, whereby state- and market-led modes of energy governance are continuously renegotiated. At another level, however, the politics of knowledge is explained here as exercised through contending ontologies of the fossil fuel resource that pivots security claims, or ‘geo-logics’, which has multiplying effects on resource materiality.

Exogenous approach to improve topic segmentation

Purpose – Topic segmentation is one of the active research fields in natural language processing. Also, many topic segmenters have been proposed. However, the current challenge of researchers is the improvement of these segmenters by using external resources. Therefore, the purpose of this paper is to integrate study and evaluate a new external semantic resource in topic segmentation. Design/methodology/approach – New topic segmenters (TSS-Onto and TSB-Onto) are proposed based on the two well-known segmenters C99 and TextTiling. The proposed segmenters integrate semantic knowledge to the segmentation process by using a domain ontology as an external resource. Subsequently, an evaluation is made to study the effect of this resource on the quality of topic segmentation along with a comparative study with related works. Findings – Based on this study, the authors showed that adding semantic knowledge, which is extracted from a domain ontology, improves the quality of topic segmentation. Moreover, TSS-Ont outperforms TSB-Ont in terms of quality of topic segmentation. Research limitations/implications – The main limitation of this study is the used test corpus for the evaluation which is not a benchmark. However, we used a collection of scientific papers from well-known digital libraries (ArXiv and ACM). Practical implications – The proposed topic segmenters can be useful in different NLP applications such as information retrieval and text summarizing. Originality/value – The primary original contribution of this paper is the improvement of topic segmentation based on semantic knowledge. This knowledge is extracted from an ontological external resource.

An ontology for description of drug discovery investigations.

The paper presents an ontology for the description of Drug Discovery Investigation (DDI).This has been developed through the use of a Robot Scientist "Eve", and in consultation with industry. DDI aims to define the principle entities and the relations in the research and development phase of the drug discovery pipeline. DDI is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. This enables DDI to be integrated with such related ontologies as the Vaccine Ontology, the Advancing Clinico-Genomic Trials on Cancer Master Ontology, etc. DDI is available at http://purl.org/ddi/wikipedia or http://purl.org/ddi/home.

Enterprise Resources Integration System for Rapid Extended Manufacturing

In order to realize rapid extended manufacturing, isomerism data integration method of enterprise resource, based on multi-dimension ontology, is proposed. Enterprise resource classified model is introduced, and process of integration and sharing of enterprise resources is analyzed. Besides, construction method of application view dimension enterprise resource ontology, life cycle dimension enterprise resource ontology and polymerization degree dimension enterprise resource ontology are discussed. Further more, entity relation diagram of enterprise resource integration is introduced, and generating and parsing mechanism of XML file about application view enterprise resources ontology is also stated. The mentioned method can resolve problems, such as enterprise resource isomerism data integration, operating authority control, and state information real-time tracking.

A fine-grained context-aware access control model for health care and life science linked data

Health Care and Life Sciences (HCLS) have long been a test-bed for the standards proposed by the W3C to build the Semantic Web. One of the challenges to HCLS Linked Data is access control. In this paper, we present a fine-grained context-aware access model for HCLS Linked Data based on Semantic Web tools. The model consists of two basic components: ontology base and access policy. Ontology base refers to a set of ontologies that include subject ontology, resource ontology, environment ontology, and action ontology. In the access policy module, we describe the access policy with eXtensible Access Control Markup Language (XACML) model, which allows users to achieve access rule reproduction by defining the semantic scope and inference rules among different entities. Results of the analysis indicate that indicates that our model expands the scopes of authorization rules for users. Inference of semantic authorization rules is also realized. These rules enable fine-grained access to data and meet the need for dynamic change of HCLS Linked Data. Finally, we show the process of authorization and present a system framework. Simulation experiments verify the acceptability of our model in protecting secured data.

Terminological and ontological resource and semantic annotations for knowledge management

In dynamic contexts, ontologies and their lexical component terminological and ontological resource or TOR have to frequently adapt to domain evolutions, new uses and new user needs. Among all depending data, ontology-based semantic annotations also are regularly updated to tag new documents or to reflect new points of view. Within the TextViz ontology-based annotation framework, we propose EvOnto: a tool and a method that supports a coherent joint change management of termino-ontologies and semantic annotations. A special attention is paid to terms and concept labels as well as quality criteria to evaluate automatic text annotations and to detect lacks in the ontology. The method defines a cyclic process: after annotation evaluation, EvOnto proposes various change operators for the TOR and, for each of them; it allows tuning the consequences of this change within the TOR and back on the annotations. In this paper, the method will be motivated and detailed. The help provided by the support tool will be illustrated in a case-study where a collection of software maintenance files are semantically indexed by a domain TOR.

Application of a capability-based adaptation methodology to a small-size production system

Today's production systems need to adapt rapidly to changing product requirements. Adaptation can be eased by formal models, representing product requirements and system capabilities, which convey the necessary information for adaptation planning activities. This paper presents an adaptation approach based on matching product requirements with resource capabilities, and applies it to a practical case study in TUT-microfactory environment. The main emphasis is placed firstly on introducing the ontological resource description, which facilitates the representation of resource capabilities. Secondly, the rules, according to which information about product requirements and resource capabilities is compared to find the match, are highlighted. The proposed approach facilitates automatic filtering, reasoning, and generation of alternative adaptation scenarios from a vast amount of resource information. As a result, less manual information handling and reasoning are required during adaptation planning.

Ontology Construction of Crop Germplasm Resources

Ontology is an efficient organization for improving integration, sharing and use efficiency of crop germplasm resources. On the basis of analyzing traditional ontology construction methods and characteristics of national crop germplasm resources, a semi-automated ontology construction method combining structured data and unstructured data was proposed. The method estab- lished initial ontology by extracting concepts and their relationship from relational database based on object-oriented approach, then, extracted concepts from unstructured web data, and enriched the semantic of these concepts using online dictionaries such as WordNet and online encyclopedia Wikipedia, so as to improve the initial ontology. Crop germplasm resources ontology model was constructed using Protege, an ontology construction tool. The experimental results showed that the method made the database resources fully utilized, the complementary role of unstructured data considered, the cost of ontology construction reduced, and the ontology more perfected. The paper discussed ontology evolution way, and pointed out the advantages and disadvantages of the study.

Part resource ontology construction approach based on heterogeneous CAD model documents

It is one of the most efficient ways to develop and extend ontology database by acquiring field concepts and knowledge contained in the existing and available data resource. A semi-automatic reverse engineering approach is proposed to construct part resource ontology based on heterogeneous CAD (Co mputer-Aided Design) model documents. Due to offer reference to automatically acquire part resource library details, the information exchange mechanism is described between part resource library and CAD system, and then the part resource ontology extraction frame and semantic model construction process are illustrated based on reverse engineering. Additionally, the part resource ontology storage model based on relational database (RDB) is proposed to fulfill efficient storage and management to OWL (Web Ontology Language) ontology. Finally, the feasibility of this approach is verified by an example for part resource ontology construction and instance extension.

Special issue on bio-ontologies and phenotypes.

The bio-ontologies and phenotypes special issue includes eight papers selected from the 11 papers presented at the Bio-Ontologies SIG (Special Interest Group) and the Phenotype Day at ISMB (Intelligent Systems for Molecular Biology) conference in Boston in 2014. The selected papers span a wide range of topics including the automated re-use and update of ontologies, quality assessment of ontological resources, and the systematic description of phenotype variation, driven by manual, semi- and fully automatic means.

Common intelligent semantic matching engines of cloud manufacturing service based on OWL-S

In order to improve the practicability of the search engine of cloud manufacturing platform in small- and medium-sized enterprises (SMEs), the paper studied the matching process’ diversity, heterogeneity, and multi-constraints between the intelligent matching engine and cloud manufacturing (CMfg) service, then established an intelligent searching engine of CMfg service in SMEs which is based on ontology language for service (OWL-S), and analyzed its matching degree quantization problems of matching process between ontology concept parameters and constraint parameters. To verify its validity, we have applied it in automobile/motorcycle accessory industry. By combining a quantization method, a matching algorithm and semantic similarity, an automobile/motorcycle accessory ontology database is established. It has fulfilled the semantic inference of the service resources ontology and has realized the valid and rapid intelligent matching of cloud searching.

Annotating Fuzzy Web Data Table Integration using ONDINE System

To design ONDINE system for loading and querying of data from the data warehouse using Ontological and Terminological Resource (OTR). The data warehouse consists of data in the table format which is to be extracted from the web documents. The primary step is to annotate the data tables that are extracted. Then the querying system is presented for simultaneous responses to the user queries using OTR.

A Web 3.0 ontology based on similarity: a step toward facilitating learning in the Big Data age

Web 3.0 technology will revolutionize the learning process, enabling data linking to connect learning resources and create ontologies for different areas of knowledge that enable ‘smart searches.’ Smart or semantic searches perceive relationships among various pieces of information and present them to the learner. Connectivism has been proposed as a theory to guide learning in this new Web 3.0 environment. This paper discusses the relevance of connectivism and then develops an ontology for learning resources. The authors propose a hybrid similarity measure to evaluate the similarity among different learning resources. The paper presents a case study that was conducted to evaluate the proposed similarity measure on education data sets and demonstrates the effectiveness of the proposed methods.

Un filosofar desde el cuerpo para la sociedad de la información

El autor examina la sociedad de la información y propone su crítica a través de la categoría de “cuerpo”, reconceptualizado como la totalidad de los aspectos físicos, biológicos, sociales y personales que somos. Incluye la noción de “cuerpos sociales” y cuestiona la era de la comunicación mediante recursos epistemológicos, ontológicos y axiológicos aplicados al estudio de la virtualidad informativa y sus alcances en el mundo actual.

Summarizing and visualizing structural changes during the evolution of biomedical ontologies using a Diff Abstraction Network

Biomedical ontologies are a critical component in biomedical research and practice. As an ontology evolves, its structure and content change in response to additions, deletions and updates. When editing a biomedical ontology, small local updates may affect large portions of the ontology, leading to unintended and potentially erroneous changes. Such unwanted side effects often go unnoticed since biomedical ontologies are large and complex knowledge structures. Abstraction networks, which provide compact summaries of an ontology’s content and structure, have been used to uncover structural irregularities, inconsistencies and errors in ontologies. In this paper, we introduce Diff Abstraction Networks (“Diff AbNs”), compact networks that summarize and visualize global structural changes due to ontology editing operations that result in a new ontology release. A Diff AbN can be used to support curators in identifying unintended and unwanted ontology changes. The derivation of two Diff AbNs, the Diff Area Taxonomy and the Diff Partial-area Taxonomy, is explained and Diff Partial-area Taxonomies are derived and analyzed for the Ontology of Clinical Research, Sleep Domain Ontology, and eagle-i Research Resource Ontology. Diff Taxonomy usage for identifying unintended erroneous consequences of quality assurance and ontology merging are demonstrated.