Ontology System Research Articles

Uncertainty Management in Knowledge Modelling

Abstract Knowledge base systems have a central role in the architecture of intelligent information systems. The most widely used implementation form is based on ontology modelling. The traditional ontology systems store common objective facts which can be managed with the traditional Boolean logic. The reasoning process is usually based on the strict descriptive logic. In the case of modelling the knowledge database of an agent, the statements are not always strict true or false. There exists some kind of uncertainty in the knowledge model. The paper summarizes the main approaches of uncertainty management and presents a new proposal for a logic model supporting uncertainty in truth value. The classical models assume that the truth value for any predicate can be given with a single value from a scalar value of a lattice domain. In the special case of fuzzy logic, the truth values are coming from the [0,1] interval. These truth values relate to the positive property. On the other hand, we can find in the literature some works arguing for the existence of negative property. In these models, a negative property p- has always a positive counterpart property p+. The proposed logic model is based on the adaption of the infinite-valued probabilistic logic to negative properties. The paper presents a prototype application of the proposed model in the domain of e-tutor systems.

Ontological approach and fuzzy modeling to describe objects of living environment

The use of ontologies and mathematical approach using fuzzy models to describe the housing environment using modern information technology is considered in the article. The aim is developing the intelligent system that is designed to assess the quality of residential environment. The determined indices are depicted as ontological system represented using Protege tool. The work result is developed ontological model of residential environment that can be used to assess the quality of apartments, houses, neighborhoods and districts. The use of modern information technology and the proposed intelligent system will simplify the work of real estate appraisers and consumers at flat choosing.

Performance Evaluation of Fuzzy based Ontology System for Identification of Malaria Disease

The disease identification from the symptoms and other detail is one of the important research area for researcher. The various ontology systems which relate the symptom and disease is evaluated by the researchers. Many time this system fail due to confusing symptom which make the fuzzy problem for classification. In this paper fuzzy based ontology system is presented. The fuzziness of the symptoms is solving by generating and optimizing the rule base. The Malaria disease has been used to evaluate the performance of classifier. The accuracy of classification on symptoms database is the key parameter used for performance evaluation of method.

Búsqueda de documentos basada en el uso de índices ontológicos creados con MapReduce

<p>Este artículo presenta un sistema de búsqueda soportado en un sistema de indexación ontológico. La técnica presentada utiliza emparejamiento de retículos. El proceso de emparejamiento se realiza entre el retículo podado con el espacio de búsqueda del corpus y el retículo con el espacio de búsqueda de la consulta. Dicho proceso permite realizar un filtrado con los documentos que deben presentarse al usuario. El sistema propuesto fue implementado utilizando el modelo de programación MapReduce. Los resultados experimentales reflejan la eficacia del sistema, al brindar al usuario una mayor correspondencia de los resultados con el dominio de búsqueda. Además, se evidencian mejoras en el rendimiento y mayor precisión en los resultados mostrados al usuario. La evaluación realizada se incluye al final del artículo. </p>

Toward the design of a nursing ontology system.

The unambiguous and consistent representation of the healthcare domain is the foundation of modernized healthcare (eg, electronic medical records). However, the nursing domain often fails to meet this requirement. In this article, we address this challenge by presenting a three-stage methodological approach that can be used to (1) capture knowledge in a nursing domain; (2) design a nursing ontology, composed of data models linked with terminology concepts in a multirelational property graph; and (3) implement and (4) evaluate the ontology. Through the feasibility, development, and evaluation phases of our methodological approach, we modeled a nursing domain (ontology) and the indices that partition the domain into an efficient, searchable space, where the solution to a nursing problem is seen as abstractly defined traversals through its graph vertices and edges. Thus, the use of the three-phase ontology development process and multirelational property graph was sufficiently comprehensive for achieving the representation of a nursing domain ontology and its instantiation.

온톨로지를 이용한 웹문서의 시맨틱 검색

사용자들에게 좀 더 정확하고 편리한 검색결과를 제공하기 위하여 정보의 구조적인 특징 등을 사용하는 시맨틱 검색의 개념이 널리 연구되고 있다. 이를 위하여, 최근의 정보검색분야와 데이터구축 분야의 연구에서는 데이터의 구조적인 표현과 검색 메카니즘을 구현하기 위하여 온톨로지를 강조하고 있다. 본 연구에서는 웹 환경에서의 검색 정확도와 만족도를 향상시키기 위하여 온톨로지를 이용한 시맨틱 검색 방법을 제안한다. 온톨로지와 KB(KnowledgeBase)를 이용하여 검색 대상을 키워드간의 관계를 유추한 사실(fact)과 관계키워드들을 지니는 웹문서들로 크게 나누고 이들을 서로 유기적으로 검색을 진행하는 시맨틱 검색 질의 처리기법을 제안하였다. 또한 결과에 대한 사용자의 검색 만족도를 높이기 위하여 결과 문서와 사실에 대한 랭킹 방법을 제안하였다. 실험을 통하여 주어진 식의 값을 달리하여 랭킹을 올바로 구현하는 요소로 키워드의 빈도와 온톨로지상의 클래스 레벨이 영향을 미치는 것을 확인 할 수 있었고, 이를 통하여 적합한 형태의 계수 값을 제시하였다. To provide efficient and correct search results, ontology which use the structure of information, is considered as a main mechanism in the semantic web. Therefore, recent research in information retrieval and data construction have emphasized the use of ontologies as a data representation and search mechanism. In this paper, we propose a semantic search method using ontology to improve search ability in web environment. Ontology and knowledge base is used to represent semantic meaning of the data and provide related web documents and facts as results. Also, search result ranking mechanism is proposed. The mechanism use cardinality of the keyword in the contents and structural information of ontology. Experimental results with several query processing indicate that different coefficient value in the expression gives different results in sample ontology system and we propose appropriate values of the coefficient.

MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT.

Non-lattice fragments are often indicative of structural anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. However, extracting the non-lattice fragments in large ontological systems is computationally expensive if not prohibitive, using a traditional sequential approach. In this paper we present a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), for extracting non-lattice fragments in large partially ordered sets and demonstrate its applicability in ontology quality assurance. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014 (each containing over 300k concepts), with an average total computing time of less than 3 hours per version. With dramatically reduced time, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies, but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). This demonstrates that fragments around non-lattice pairs exhibit significantly higher rates of change in the process of ontological evolution.

Forms of Thought, by E. J. Lowe.

It was with great sadness that I heard of the death of E. J. Lowe in early January 2014. I have learned a great deal from his writings, and I very much regret not having completed the review which follows in time for him to comment on it. His contributions to the philosophical debates in which he partook, and which he did so much to shape, will be sorely missed. Lowe’s recent book Forms of Thought is subtitled ‘A Study in Philosophical Logic’. The preface and first chapter lay out what is meant by this: Lowe claims that the underlying aim of the discipline in which he is engaged (philosophical logic) is to ‘reveal forms of thought, at least to the extent that thoughts are propositional in character and thus capable of standing in logical relations to one another’ (p. ix); though he suggests that ‘in practice that task must be approached by investigating the structure of sentences in natural language — since it is in such sentences that our thoughts are clothed and communicated’ (p. ix). But the book, it seems to me, is equally an essay in what P. F. Strawson (Individuals, London: Methuen, 1959) called descriptive metaphysics: that is, it is an attempt not only to characterize our ordinary ways of thinking and talking about the world, but also to vindicate them as fundamentally correct. Describing what is to come, Lowe writes: I criticize the ontological presuppositions of the type of formal predicate logic that contemporary philosophers have inherited from the founders of modern quantificational logic, notably Gottlob Frege and Bertrand Russell, and propose some major reformations. This carries … forward the task … of constructing a system of formal logic which perspicuously reflects the neo-Aristotelian ontological presuppositions of my own preferred system of categorial ontology (p. 3)

An ontological system based on MODIS images to assess ecosystem functioning of Natura 2000 habitats: A case study for Quercus pyrenaica forests

The implementation of the Natura 2000 network requires methods to assess the conservation status of habitats. This paper shows a methodological approach that combines the use of (satellite) Earth observation with ontologies to monitor Natura 2000 habitats and assess their functioning. We have created an ontological system called Savia that can describe both the ecosystem functioning and the behaviour of abiotic factors in a Natura 2000 habitat. This system is able to automatically download images from MODIS products, create indicators and compute temporal trends for them. We have developed an ontology that takes into account the different concepts and relations about indicators and temporal trends, and the spatio-temporal components of the datasets. All the information generated from datasets and MODIS images, is stored into a knowledge base according to the ontology. Users can formulate complex questions using a SPARQL end-point. This system has been tested and validated in a case study that uses Quercus pyrenaica Willd. forests as a target habitat in Sierra Nevada (Spain), a Natura 2000 site. We assess ecosystem functioning using NDVI. The selected abiotic factor is snow cover. Savia provides useful data regarding these two variables and reflects relationships between them.

RehabRobo-Onto: Design, development and maintenance of a rehabilitation robotics ontology on the cloud

Representing the available information about rehabilitation robots in a structured form, as an ontology, facilitates access to various kinds of information about the existing robots, and thus it is important both from the point of view of rehabilitation robotics and from the point of view of physical medicine. Rehabilitation robotics researchers can learn various properties of the existing robots and access to the related publications to further improve the state-of-the-art. Physical medicine experts can find information about rehabilitation robots and related publications (possibly including results of clinical studies) to better identify the right robot for a particular therapy or patient population. Therefore, considering also the advantages of ontologies and ontological reasoning, such as interoperability of various heterogeneous knowledge resources (e.g., patient databases or disease ontologies), such an ontology provides the underlying mechanisms for translational physical medicine, from bench-to-bed and back, and personalized rehabilitation robotics. With these motivations, the first formal rehabilitation robotics ontology, called RehabRobo-Onto, is designed and developed, collaborating with experts in robotics and in physical medicine. A web based software (called RehabRobo-Query) with an easy-to-use intelligent user-interface is also built. RehabRobo-Query allows robot designers to add/modify information about their rehabilitation robots to/from RehabRobo-Onto. The ontology system consisting of RehabRobo-Onto and RehabRobo-Query is made available on the cloud, utilizing Amazon Web services, to provide a reliable environment for access, development and maintenance of RehabRobo-Onto by rehabilitation robot designers and physical medicine experts around the world. HighlightsRehabRobo-Onto is the first formal rehabilitation robotics ontology.It is open access on the cloud via Amazon EC2 Web services.It is interoperable with other knowledge resources (e.g, disease ontologies).It supports query answering using DL reasoners and Semantic Web technologies.Rehabilitation robotics researchers and physical medicine experts are potential users.

Commentary on Shimoyama et al. (2012): three ontologies to define phenotype measurement data.

Commentary on Shimoyama et al. (2012): three ontologies to define phenotype measurement data.

Canonical Sensor Ontology Builder Based on ISO/IEC 11179 for Sensor Network Environments: A Standardized Approach

The advancement of sensor technology has led to an explosive increase in sensors. It causes semantic heterogeneity problems, and much research has focused on sensor ontology building to solve the problems. However, there are still remaining several issues, and one of the most critical issues is about a method for progressive and dynamic concepts management and reuse of sensor ontology. This paper proposes an ontology generation system based on ISO/IEC 11179–MDR (metadata registry). The proposed system is referred to as the Canonical Sensor Ontology Builder (CaSOB) and can create ontologies by reusing the common concepts registered in a canonical sensor ontology concept registry, an MDR. This paper defines a mapping model and processes to create ontology with the concepts registered in an MDR. Our proposal provides many advantages such as high standardization, consistent concept usage, and easy semantic exchange. Therefore, CaSOB facilitates the high quality sensor ontology creation and reduces the costs of sensor ontology integration and system development.

An ontological approach for reliable data integration in the industrial domain

Ontologies are structural components of modern information systems. The taxonomy, the core of an ontology, is a delicate balance between adequacy considerations, minimal commitments and implementation concerns. However, ontological taxonomies can be quite restrictive and entities that are commonly used in production and services might not find room in a official or de facto standard or ontological system. This mismatch between the company's view and the ontological constraints can limit or even jeoparize the adoption of modern formal ontologies in industry. We study the roots of this problem and individuate a general set of principles to relate the ontology and those non-ontological entities that are yet important for the core business of the company. We then introduce a theoretically sound and formally robust approach to expand a given ontology with new dependency relations, which make available information regarding the non-ontological entities without affecting the consistency of the overall information system.

Product Design Ontology System Based on FBS-API

Designontology plays an important role in modern multi-party collaborations andknowledge-intensive designs. In this paper, a product design ontology system isproposed by analyzing and deconstructing the design function–behavior–structure(FBS) model and geometry application programming interfaces (APIs). GeometryAPIs and surface behavior are considered minimum structure units and concretefunction realization, respectively. APIs and their surface behavior are definedto build the semantic connection among functions, behavior, and structures andrefine further the ontology of FBS design. According to some inference rules, designontology can be used to obtain automatically or semi-automatically thepreliminary product function and structure. The studied cases prove that therepresentation of the design knowledge based on the FBS-API ontology overcomesthe limit of mere word conventions and is more conducive to the quantizationand derivation of product design.

A survey on the complementarity between database and ontologies: principles and research areas

This paper presents a survey on the complementarity between databases and ontologies. It interests semantic web and database communities. Ontologies can help in overcoming the drawbacks of DBs and vice-versa. We conducted a deep analysis, which reveals that the collaboration between these two disciplines can be done in five different ways: facilitating the database design, increasing their semantics for information retrieval, integration and maintenance, designing ontologies from existing databases, and allowing storage of large number of instances in ontological systems. We present in this paper the concepts related to this field, the reasons for this rapprochement and a state-of-the-art on existing approaches in this area. For each of the axes presented, we will present the axis, underlying issues and cite relevant research. Originality of our work comes from the fact that it covers the whole field of rapprochement between databases and ontologies. Therefore, it provides the reader, who may not be very familiar with this domain of research, with an introduction to axes in this research and with pointers to different research projects.

An ontological approach to knowledge management for sustainable nuclear decommissioning

Nuclear decommissioning design and operational knowledge may remain relevant over many decades. Designing sustainable operations today requires meaningful simulation of future events, which in turn relies on the accurate representation of all relevant current knowledge. In decommissioning, human agents may be as important for maintaining operational safety as technical systems, so simulations must represent not just technical but tacit knowledge (embedded in practice) and the contextual and perceptual aspects of knowledge – i.e. how the meaning of data changes with the circumstances and viewpoint of stakeholders. We propose that this detail may be captured by ontological knowledge systems, which are augmenting traditional archives, databases or operational flowcharts in other highly interlinked, multidisciplinary, dynamic and highly specialised fields. Using the example of waste transport modelling, this study discusses how a coherent ontology unifying knowledge, physics and simulations could facilitate the design, assessment and communication of sustainable decommissioning.

Ontologies for Software Project Management: A Review

Software Project Management is a knowledge intensive process that can benefit substantially from ontology development and ontology engineering. Ontology development could facilitate or improve substantially the software development process through the improvement of knowledge management, the increase of software and artefacts reusability, and the establishment of internal consistency within project management processes of various phases of software life cycle. A large number of ontologies have been developed attempting to address various software engineering aspects, such as requirements engineering, components reuse, domain modelling, etc. In this paper, we present a systematic literature review focusing on software project management ontologies. The literature review, among other, has identified lack of standardization in terminology and concepts, lack of systematic domain modelling and use of ontologies mainly in prototype ontology systems that address rather limited aspects of software project management processes.

Fusion of Large-Scale Genomic Knowledge and Frequency Data Computationally Prioritizes Variants in Epilepsy

Curation and interpretation of copy number variants identified by genome-wide testing is challenged by the large number of events harbored in each personal genome. Conventional determination of phenotypic relevance relies on patterns of higher frequency in affected individuals versus controls; however, an increasing amount of ascertained variation is rare or private to clans. Consequently, frequency data have less utility to resolve pathogenic from benign. One solution is disease-specific algorithms that leverage gene knowledge together with variant frequency to aid prioritization. We used large-scale resources including Gene Ontology, protein-protein interactions and other annotation systems together with a broad set of 83 genes with known associations to epilepsy to construct a pathogenicity score for the phenotype. We evaluated the score for all annotated human genes and applied Bayesian methods to combine the derived pathogenicity score with frequency information from our diagnostic laboratory. Analysis determined Bayes factors and posterior distributions for each gene. We applied our method to subjects with abnormal chromosomal microarray results and confirmed epilepsy diagnoses gathered by electronic medical record review. Genes deleted in our subjects with epilepsy had significantly higher pathogenicity scores and Bayes factors compared to subjects referred for non-neurologic indications. We also applied our scores to identify a recently validated epilepsy gene in a complex genomic region and to reveal candidate genes for epilepsy. We propose a potential use in clinical decision support for our results in the context of genome-wide screening. Our approach demonstrates the utility of integrative data in medical genomics.

Validation of an ontological medical decision support system for patient treatment using a repository of patient data

In this article, we begin by presenting OMeD, a medical decision support system, and argue for its value over purely probabilistic approaches that reason about patients for time-critical decision scenarios. We then progress to present Holmes, a Hybrid Ontological and Learning MEdical System which supports decision making about patient treatment. This system is introduced in order to cope with the case of missing data. We demonstrate its effectiveness by operating on an extensive set of real-world patient health data from the CDC, applied to the decision-making scenario of administering sleeping pills. In particular, we clarify how the combination of semantic, ontological representations, and probabilistic reasoning together enable the proposal of effective patient treatments. Our focus is thus on presenting an approach for interpreting medical data in the context of real-time decision making. This constitutes a comprehensive framework for the design of medical recommendation systems for potential use by medical professionals and patients both, with the end result being personalized patient treatment. We conclude with a discussion of the value of our particular approach for such diverse considerations as coping with misinformation provided by patients, performing effectively in time-critical environments where real-time decisions are necessary, and potential applications facilitating patient information gathering.

Rapid Service-Oriented business process generation method based on ontology

Service-oriented business process generation is a key activity in the Service-Oriented Architecture (SOA) business lifecycle, and most of the other activities such as application execution depend on the business process being developed. After the business requirements are acquired, a developer has to use specific programming technologies to orchestrate web services to generate a deployable business process. It is time-consuming to specify all the business processes from low-level web services, especially for an enterprise that focuses on a series of similar businesses. This paper proposes a rapid service-oriented business process generation method with domain-specific assets specified in ontology systems. Assets with different levels of granularity are reused to refine the high level business process framework for executable business processes using the Business Process Executional Language (BPEL). The new methodology significantly simplifies service-oriented business process generation by reusing assets to construct business processes. A business process generation tool is also implemented to support the efficient visual design of SOA processes with the proposed method. This paper verifies the proposed method using a shipment tracking case. The studies show that the number of reusable assets increases significantly as these projects progress, and the business process generation speed also increases at the same time.