Extension Of Ontology Research Articles

Knowledge Modeling of Product Data Based on Fuzzy Ontology

Ontology is the basis of knowledge modeling on the Semantic Web, and fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. Ontology-base knowledge modeling of product data management (PDM) is meaningful for product design and trade etc. In order to handle fuzzy phenomenon and uncertainty of product knowledge, this paper proposes a series of fuzzy ontology models that consists of fuzzy domain ontology and fuzzy linguistic variable ontologies. Then, a fuzzy ontology framework is presented, including three parts: concepts, properties of concepts and values of properties. The application, which uses fuzzy ontology to model product knowledge, shows that these models can overcome the localization of other fuzzy ontology models, and this research facilitates the fuzzy knowledge sharing and reuse for PDM on the Semantic Web.

Semi-automated ontology generation within OBO-Edit

Motivation: Ontologies and taxonomies have proven highly beneficial for biocuration. The Open Biomedical Ontology (OBO) Foundry alone lists over 90 ontologies mainly built with OBO-Edit. Creating and maintaining such ontologies is a labour-intensive, difficult, manual process. Automating parts of it is of great importance for the further development of ontologies and for biocuration.Results: We have developed the Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG), a system which supports the creation and extension of OBO ontologies by semi-automatically generating terms, definitions and parent–child relations from text in PubMed, the web and PDF repositories. DOG4DAG is seamlessly integrated into OBO-Edit. It generates terms by identifying statistically significant noun phrases in text. For definitions and parent–child relations it employs pattern-based web searches. We systematically evaluate each generation step using manually validated benchmarks. The term generation leads to high-quality terms also found in manually created ontologies. Up to 78% of definitions are valid and up to 54% of child–ancestor relations can be retrieved. There is no other validated system that achieves comparable results.By combining the prediction of high-quality terms, definitions and parent–child relations with the ontology editor OBO-Edit we contribute a thoroughly validated tool for all OBO ontology engineers.Availability: DOG4DAG is available within OBO-Edit 2.1 at http://www.oboedit.orgContact: thomas.waechter@biotec.tu-dresden.de;Supplementary Information: Supplementary data are available at Bioinformatics online.

A linguistic ontology of space for natural language processing

We present a detailed semantics for linguistic spatial expressions supportive of computational processing that draws substantially on the principles and tools of ontological engineering and formal ontology. We cover language concerned with space, actions in space and spatial relationships and develop an ontological organization that relates such expressions to general classes of fixed semantic import. The result is given as an extension of a linguistic ontology, the Generalized Upper Model, an organization which has been used for over a decade in natural language processing applications. We describe the general nature and features of this ontology and show how we have extended it for working particularly with space. Treaitng the semantics of natural language expressions concerning space in this way offers a substantial simplification of the general problem of relating natural spatial language to its contextualized interpretation. Example specifications based on natural language examples are presented, as well as an evaluation of the ontology's coverage, consistency, predictive power, and applicability.

A Geographic Information System Framework for the Management of Sensor Deployments

A prototype Geographic Information System (GIS) framework has been developed to map, manage, and monitor sensors with respect to other geographic features, including land base and in-plant features. The GIS framework supports geographic placement and subsequent discovery, query, and tasking of sensors in a network-centric environment using Web services. The framework couples the GIS feature placement logic of sensors with an extensible ontology which captures the capabilities, properties, protocols, integrity constraints, and other parameters of interest for a large variety of sensor types. The approach is significant in that custom, GIS-based interfaces can be rapidly developed via the integration of sensors and sensor networks into applications without having detailed knowledge of the sensors’ underlying device drivers by leveraging service-oriented computing infrastructure within the GIS framework.

Supporting Ontology-Based Semantic Annotation of Business Processes with Automated Suggestions

Annotation of Business Processes with semantic tags taken from a domain ontology is beneficial to several activities conducted on Business Processes, such as comprehension, documentation, analysis and evolution. On the other hand, the task of semantically annotating Business Processes is time-consuming and far from trivial. The authors support Business Process designers in the annotation of process elements by automatically suggesting candidate concepts. The annotation suggestions are computed on the basis of a similarity measure between the text information associated with process element labels and the ontology concepts. In turn, this requires support for the disambiguation of terms appearing in ontology concepts, which admit multiple linguistic senses, and for ontology extension, when the available concepts are insufficient.

Fuzzy Multi-Attribute Decision Making-Based Algorithm for Semantic Web Service Composition

Choosing the global optimal execution plan is an important process in the semantic Web service composition. The plan selection based on QoS is still challenging because the heterogeneous QoS values make data aggregation and decision making hard. This paper presents a novel Fuzzy Multi-attribute decision making-based semantic Web service Composition algorithm (FuMuCom) to solve the above difficulties for the first time. FuMuCom takes all possible QoS expression types (real number, interval and linguistic expression) into consideration. It includes three main steps: defuzzifying linguistic data, normalizing the decision matrix and evaluating alternatives synthetically. Other contributions of the paper include an extensible QoS ontology to express the heterogeneous QoS values, an ontology evolution strategy for aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach.

Modeling and querying provenance by extending CIDOC CRM

This paper elaborates on the problem of modeling provenance for both physical and digital objects. In particular it discusses provenance according to OAIS (ISO 14721:2003) and how it relates with the conceptualization of CIDOC CRM ontology (ISO 21127:2006). Subsequently it introduces an extension of the CIDOC CRM ontology, able to capture the modeling and the query requirements regarding the provenance of digital objects. Over this extension the paper provides a number of indicative examples of modeling provenance in various domains. Subsequently, it introduces a number of indicative provenance query templates, and finally it describes an implementation using Semantic Web technologies.

Anomalies in ontologies with rules

For the development of practical semantic applications, ontologies are commonly used with rule extensions. Prominent examples of semantic applications not only are Semantic Wikis, Semantic Desktops, but also advanced Web Services and agents. The application of rules increases the expressiveness of the underlying knowledge in many ways. Likewise, the integration not only creates new challenges for the design process of such ontologies, but also existing evaluation methods have to cope with the extension of ontologies by rules. Since the verification of Owl ontologies with rule extensions is not tractable in general, we propose to verify ontologies at the symbolic level by using a declarative approach: With the new language Datalog ⋆, known anomalies can be easily specified and tested in a compact manner. We introduce supplements to existing verification techniques to support the design of ontologies with rule enhancements, and we focus on the detection of anomalies that especially occur due to the combined use of rules and ontological definitions.

Anomalies in Ontologies with Rules

For the development of practical semantic applications, ontologies are commonly used with rule extensions. Prominent examples of semantic applications are Semantic Wikis, Semantic Desktops, but also advanced Web Services and agents. The application of rules increases the expressiveness of the underlying knowledge in many ways. Likewise, the integration creates new challenges for the design process of such ontologies, but also existing evaluation methods have to cope with the extension of ontologies by rules. Since the verification of OWL ontologies with rule extensions is not tractable in general, we propose to verify ontologies at the symbolic level by using a declarative approach: With the new language DATALOG, known anomalies can be easily specified and tested in a compact manner. We introduce supplements to existing verification techniques to support the design of ontologies with rule enhancements, and we focus on the detection of anomalies that especially occur due to the combined use of rules and ontological definitions.

NeuronBank: a tool for cataloging neuronal circuitry

The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models.

GeMInA, Genomic Metadata for Infectious Agents, a geospatial surveillance pathogen database.

The Gemina system (http://gemina.igs.umaryland.edu) identifies, standardizes and integrates the outbreak metadata for the breadth of NIAID category A–C viral and bacterial pathogens, thereby providing an investigative and surveillance tool describing the Who [Host], What [Disease, Symptom], When [Date], Where [Location] and How [Pathogen, Environmental Source, Reservoir, Transmission Method] for each pathogen. The Gemina database will provide a greater understanding of the interactions of viral and bacterial pathogens with their hosts and infectious diseases through in-depth literature text-mining, integrated outbreak metadata, outbreak surveillance tools, extensive ontology development, metadata curation and representative genomic sequence identification and standards development. The Gemina web interface provides metadata selection and retrieval of a pathogen's; Infection Systems (Pathogen, Host, Disease, Transmission Method and Anatomy) and Incidents (Location and Date) along with a hosts Age and Gender. The Gemina system provides an integrated investigative and geospatial surveillance system connecting pathogens, pathogen products and disease anchored on the taxonomic ID of the pathogen and host to identify the breadth of hosts and diseases known for these pathogens, to identify the extent of outbreak locations, and to identify unique genomic regions with the DNA Signature Insignia Detection Tool.

An OWL-DL Ontology for Classification of Lipids

Lipids can be systematically classified according to functional properties, structural features, biochemical origin or biological system. However Lipid nomenclature has yet to become a robust research tool since no rigorous definitions exist for membership of specific lipid classes. Lipids need to be defined in a manner that is systematic yet at the same time semantically explicit. We report on the reuse of existing lipid nomenclature, ontology describing chemical structure and the extension of the OWL-DL Lipid Ontology to support the classification of lipid molecules. We applied definitions, DL-axioms, to describe lipids classes and illustrate suitability of the ontology for the classification of Fatty Acyl lipids and Mycolic acids.

An OWL-DL Ontology for Classification of Lipids

AbstractLipids can be systematically classified according to functional properties, structural features, biochemical origin or biological system. However Lipid nomenclature has yet to become a robust research tool since no rigorous definitions exist for membership of specific lipid classes. Lipids need to be defined in a manner that is systematic yet at the same time semantically explicit. We report on the reuse of existing lipid nomenclature, ontology describing chemical structure and the extension of the OWL-DL Lipid Ontology to support the classification of lipid molecules. We applied definitions, DL-axioms, to describe lipids classes and illustrate suitability of the ontology for the classification of Fatty Acyl lipids and Mycolic acids.

An Ontology Enhancement Framework to Accommodate Imprecise Concepts and Relations

In this paper, we propose an ontology enhancement framework to accommodate imprecise concepts and their inter-relations mined from text documents. The proposed framework is modeled as a fuzzy ontology structure to represent concept descriptor as a fuzzy relation which encodes the degree of a property value using a fuzzy membership function. In our application, the fuzzy membership function is determined through text mining. Other than concept descriptors, the inter-concept relations in the ontology are also associated a fuzzy strength. The strength of association between two concepts determines the degree of association between the concepts. The fuzzy ontology with fuzzy concepts and fuzzy relations is an extension of the domain ontology with crisp concepts and relations which is more suitable to describe the domain knowledge for solving uncertainty reasoning problems. The applicability of the fuzzy ontology structure in mining and managing imprecise knowledge from biomedical text documents has been thoroughly experimented. The fuzzy ontology can later be used for information curation to answer imprecise queries posed at multiple levels of specificities along the underlying ontology.

Using Domain Ontology in a Semantic Blogging System for Construction Professionals

Smooth communication is essential for the success of construction projects. As an easy-to-use, context-rich, and high-capacity communication tool, blogging is gaining popularity in construction industry. In this paper, the features of blogging technology and how it could benefit construction organizations are presented. To further improve the effectiveness of blogging technology in information and knowledge sharing, an ontology-based semantic blogging system is proposed. Semantic blogging is an extension of conventional blogging and ontology is the key enabling technology for it. Domain-ontology-based semantic blogging site is composed of a network of concepts, which are clearly defined and interlinked according to their context and bound to certain behaviors. This paper reports how the e-Cognos ontology was implemented into a blogging system and how the system functions to process its contents. The paper concludes that using ontology-based semantic blogging site can greatly enhance information sharing between construction professionals and it is a very promising tool for construction communities to publish and share their experience.

REA Modeling of Mining Companies

ABSTRACT: This research paper applies the resource-event-agent (REA) framework to model the unique patterns, in both the REA accountability and policy infrastructures, of the mining enterprise domain. A unique resource in this domain is the mineral resource (MinResc), and the acquisition and development of MinResc to prepare it for the mining conversion process requires a unique information acquisition event to create and expand an information resource entity. The physical mineral deposit entity set and the intangible information entity set are thus aggregated into a more abstract and more valuable MinResc resource. The aggregation of a physical resource and an intangible information resource into a more certain and more valuable physical resource is an extension of the REA ontology that has applications in enterprise domains outside of mining.

Infrastructure for dynamic knowledge integration—Automated biomedical ontology extension using textual resources

We present a novel ontology integration technique that explicitly takes the dynamics and data-intensiveness of e-health and biomedicine application domains into account. Changing and growing knowledge, possibly contained in unstructured natural language resources, is handled by application of cutting-edge Semantic Web technologies. In particular, semi-automatic integration of ontology learning results into a manually developed ontology is employed. This integration bases on automatic negotiation of agreed alignments, inconsistency resolution and natural language generation methods. Their novel combination alleviates the end-user effort in the incorporation of new knowledge to large extent. This allows for efficient application in many practical use cases, as we show in the paper.

Developing a modular hydrogeology ontology by extending the SWEET upper-level ontologies

Upper-level ontologies comprise general concepts and properties which need to be extended to include more diverse and specific domain vocabularies. We present the extension of NASA's Semantic Web for Earth and Environmental Terminology (SWEET) ontologies to include part of the hydrogeology domain. We describe a methodology that can be followed by other allied domain experts who intend to adopt the SWEET ontologies in their own discipline. We have maintained the modular design of the SWEET ontologies for maximum extensibility and reusability of our ontology in other fields, to ensure inter-disciplinary knowledge reuse, management, and discovery. The extension of the SWEET ontologies involved identification of the general SWEET concepts (classes) to serve as the super-class of the domain concepts. This was followed by establishing the special inter-relationships between domain concepts (e.g., equivalence for vadose zone and unsaturated zone), and identifying the dependent concepts such as physical properties and units, and their relationship to external concepts. Ontology editing tools such as SWOOP and Protégé were used to analyze and visualize the structure of the existing OWL files. Domain concepts were introduced either as standalone new classes or as subclasses of existing SWEET ontologies. This involved changing the relationships (properties) and/or adding new relationships based on domain theories. In places, in the Owl files, the entire structure of the existing concepts needed to be changed to represent the domain concept more meaningfully. Throughout this process, the orthogonal structure of SWEET ontologies was maintained and the consistency of the concepts was tested using the Racer reasoner. Individuals were added to the new concepts to test the modified ontologies. Our work shows that SWEET ontologies can successfully be extended and reused in any field without losing their modular or reference structure, or disrupting their URI links.

Knowledge management via ontology development in accounting

PurposeThis paper seeks to develop an ontological approach, in order to make it possible to share a common understanding of accounting theory, in this case, the specific structure of the profit and loss account among people or software agents.Design/methodology/approachThis paper presents an ontology methodology (the Net technique) which represents a semi‐structured element in the domain knowledge of accounting. More specifically, ontology will be used to explain the profit and loss account as a representation of the potential use of this methodology.FindingsTo support ontology effectively, a strong accounting information support system in the organization is necessary. The ontology may be used by employees to navigate the information repository of an organization for the effective coordination. In addition, it might be possible for the WWW to be used to generate data, information and knowledge in the accounting domain.Practical implicationsSoftware agents could extract and aggregate accounting information from numerous web sites, which in turn might answer research questions or be used as input data for other applications.Originality/valueThe development of ontology expands the researcher's ability to generate information by using search methods beyond simple keywords. If only keywords are used in internet searches, then information that is retrieved will often lack the precision necessary for generating quality information. Therefore, in order to retrieve quality information more quickly and accurately, a broader and more extensive ontology development is required.

Client Provider Collaboration for Service Bundling

Abstract —The key requirement for a service industry organization to reach competitive advantages through product diversification is the existence of a well defined method for building service bundles. Based on the idea that the quality of a service or its value is given by the difference between expectations and perceptions, we draw the main components of a frame that aims to support the client and the provider agent in an active collaboration meant to co-create service bundles. Following e3-value model, we structure the supporting knowledge around the relation between needs and satisfying services. We deal with different perspectives about quality through an ontological extension of Value Based Argumentation. The dialog between the client and the provider takes the form of a persuasion whose dynamic object is the current best configuration. Our approach for building service packages is a demand driven approach, allowing progressive disclosure of private knowledge. Index Terms —Argumentation over preferences, Customer needs, Service configuration, Service offering, Web services