DOCSLIB.ORG

A Core Ontology for the Semantic Representation of Research

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Core Ontology for the Semantic Representation of Research Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com ProcediaScienceDirect Computer Science 00 (2018) 000–000 ProcediaProcedia Computer Computer Science Science 137 (2018) 00 (2018) 151–162 000–000 www.elsevier.com/locate/procedia Procedia Computer Science 00 (2018) 000–000 www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia SEMANTiCS 2018 – 14th International Conference on Semantic Systems SEMANTiCS 2018Procedia – 14th Computer International Science 00 (2018) Conference 000–000 on Semantic Systems SemSur:SEMANTiCS A Core 2018 Ontology – 14th International for the Conference Semantic on Representation Semanticwww.elsevier.com/locate/procedia Systems of SemSur: A Core Ontology for the Semantic Representation of SemSur:SEMANTiCS A Core 2018 Ontology – 14thResearch International for the Findings Conference Semantic on Representation Semantic Systems of Research Findings a,b, a c,d e Said Fathalla ∗, SaharResearch Vahdati , Findings Sören Auer , Christoph Lange SemSur: A Corea,b, Ontology fora the Semanticc,d Representatione of Said Fathallaa ∗, Sahar Vahdati , Sören Auer , Christoph Lange a,b,Smart Data Analytics (SDA),a University of Bonn,c,d Germany e Said FathallaaSmartb∗Faculty, SaharData AnalyticsofResearch Science, Vahdati (SDA), University, UniversityFindings Sören of Alexandria, Auer of Bonn, Egypt Germany, Christoph Lange cL3Sa ResearchbFaculty Center, of Science, Leibniz University University of Alexandria, of Hannover, Egypt Germany a,b,Smart Data Analytics (SDA),a University of Bonn,c,d Germany e Said FathalladTIB LeibnizcL3S Information Researchb∗Faculty, Sahar Center, of Center Science, Vahdati Leibniz for University Science University, Sören and of Alexandria, Technology, of Auer Hannover, Egypt Hannover,,Germany Christoph Germany Lange dTIB LeibnizcL3S Information Research Center, CentereFraunhofer Leibniz for Science UniversityIAIS, and Germany Technology, of Hannover, Hannover, Germany Germany aSmart Data Analytics (SDA), University of Bonn, Germany dTIB Leibniz Information CentereFraunhofer for Science IAIS, and Germany Technology, Hannover, Germany bFaculty of Science, University of Alexandria, Egypt eFraunhofer IAIS, Germany cL3S Research Center, Leibniz University of Hannover, Germany d Abstract TIB Leibniz Information Center for Science and Technology, Hannover, Germany e Abstract Fraunhofer IAIS, Germany The way how research is communicated using text publications has not changed much over the past decades. We have Abstract Thethe vision way how that research ultimately is communicated researchers will using work text on publications a common structured has not changed knowledge much base over comprising the past decades. comprehensive We have Thethesemantic vision way how and that researchmachine-comprehensible ultimately is communicated researchers will descriptions using work text on publications ofa common their research, structured has not thus changed knowledgemaking much research base over comprising the contributions past decades. comprehensive more We trans- have thesemanticparentAbstract vision and and that comparable. machine-comprehensible ultimately We researchers present the will descriptions SemSur work ontology on ofa common their for research, semantically structured thus capturing knowledgemaking research the base information comprising contributions commonly comprehensive more trans-found Thesemanticparentin survey way and how and and comparable. researchmachine-comprehensible review articles. is We communicated present SemSur the isdescriptions SemSurusing able text to ontology represent publications of their for scientific research, semantically has not results thus changed capturing making and much to research publish the over information the contributions them past in decades. commonlya comprehensive more We trans-found have theparentinknowledge survey vision and and that graph,comparable. review ultimately which articles. We provides researchers present SemSur an the efficientwill is SemSur able work to overview ontology on represent a common of for scientific a semantically research structured results field, capturing knowledge and and to to publish the compare base information comprising them research in commonlya comprehensive findings found with semanticinknowledgerelated survey works and and graph, machine-comprehensible in review a structured which articles. provides way, SemSur thus an efficient isdescriptions saving able to researchers overview represent of their of a scientific research,a significant research results thus amountfield, making and and of toto time research publish compare and contributions themeffort. research in The a comprehensive new findings more release trans- with of parentknowledgerelatedSemSur and works covers graph,comparable. in more a structured which domains, We provides present way, defines thus an the better efficient savingSemSur alignment researchers overview ontology with of for a a significant semanticallyexternal research ontologies amountfield, capturing and of andto time the rulescompare and information for effort. eliciting research The commonly implicit new findings release know- found with of inrelatedSemSurledge. survey We works covers and discuss in review more a possible structured domains, articles. applications way, SemSurdefines thus better is andsaving able present alignment to researchers represent an evaluation with a scientific significant external of results our ontologies amount approach and ofand to time with publish rules and the for themeffort. retrospective, eliciting in The a comprehensiveimplicit new exemplary release know- of knowledgeSemSurledge.semantification We covers discuss graph, more of possible a which survey. domains, provides applications We defines demonstrate an better efficient and present alignmentthe overview utility an evaluationwith of of the a external research SemSur of our ontologies ontology field, approach and to and to answer with rulescompare the forqueries retrospective, eliciting research about implicit findings the exemplary different know- with relatedledge.semantificationresearch We works contributions discuss in of a possible astructured survey. covered applications We way, by demonstrate the thus survey. andsaving present the SemSur researchers utility an is evaluation of currently thea significant SemSur of used our ontology amount and approach maintained of to time answer with and the at queriesOpenResearch.org effort. retrospective, about The new the exemplary release different. of semantificationresearch contributions of a survey. covered We by demonstrate the survey. the SemSur utility is of currently the SemSur used ontology and maintained to answer at queriesOpenResearch.org about the different. ©SemSur 2018 The covers Authors. more Published domains, by defines Elsevier better B.V. alignment with external ontologies and rules for eliciting implicit know- researchKeywords: contributionsSemSur Ontology, covered Semantic by the Metadata survey. SemSur Enrichment, is currently SWRL rules, used andScholarly maintained Communication, at OpenResearch.org Semantic Publishing,. ThisKeywords:ledge. is Wean open discussSemSur access possible Ontology, article under applications Semantic the CC Metadata BY-NC-ND and present Enrichment, license an evaluation (https://creativecommons.org/licenses/by-nc-nd/4.0/ SWRL ofrules, our Scholarly approach Communication, with the retrospective, Semantic) Publishing,exemplary Peer-reviewKeywords:semantification underSemSur ofresponsibility a Ontology, survey. We Semanticof the demonstrate scientific Metadata committee the Enrichment, utility of ofthe the SWRLSEMANTiCS SemSur rules, ontology Scholarly2018 – to14th Communication, answer International queries Conference Semantic about the Publishing,on different Semantic Systems.research contributions covered by the survey. SemSur is currently used and maintained at OpenResearch.org. Keywords: SemSur Ontology, Semantic Metadata Enrichment, SWRL rules, Scholarly Communication, Semantic Publishing, 1. Introduction 1. Introduction 1.SemSur, Introduction the Semantic Survey Ontology, is an ontology for describing research problems, approaches, implementationsSemSur, the Semantic and evaluations Survey in Ontology, a structured is an and ontology comparable for describing way. An initial research version problems, of SemSur approaches, [8] was createdimplementations1.SemSur, Introduction for ourthe approachSemantic and evaluations towards Survey in Ontology, representing a structured is an research and ontology comparable findings for describing as way. a knowledge An initial research version graph problems, and of SemSur has approaches, now [8] been was substantiallycreatedimplementations for our improved approach and evaluations and towards expanded. in representing a structured Without research SemSur,and comparable findings the preferred as way. a knowledge An way initial of providing version graph and of researchers SemSur has now [8]been with was ansubstantiallycreatedSemSur, overview for ourthe of improved aapproach Semantic field and and towards Survey enabling expanded. Ontology, representing them Without to is compare an research SemSur, ontology research findings the for preferred describing results as a knowledge way was research ofvia providingsurvey graph problems, and articles researchers has approaches,. now However,been with preparingimplementationsansubstantially
Load more

Recommended publications
  • Semantics Developer's Guide
    MarkLogic Server Semantic Graph Developer’s Guide 2 MarkLogic 10 May, 2019 Last Revised: 10.0-8, October, 2021 Copyright © 2021 MarkLogic Corporation. All rights reserved. MarkLogic Server MarkLogic 10—May, 2019 Semantic Graph Developer’s Guide—Page 2 MarkLogic Server Table of Contents Table of Contents Semantic Graph Developer’s Guide 1.0 Introduction to Semantic Graphs in MarkLogic ..........................................11 1.1 Terminology ..........................................................................................................12 1.2 Linked Open Data .................................................................................................13 1.3 RDF Implementation in MarkLogic .....................................................................14 1.3.1 Using RDF in MarkLogic .........................................................................15 1.3.1.1 Storing RDF Triples in MarkLogic ...........................................17 1.3.1.2 Querying Triples .......................................................................18 1.3.2 RDF Data Model .......................................................................................20 1.3.3 Blank Node Identifiers ..............................................................................21 1.3.4 RDF Datatypes ..........................................................................................21 1.3.5 IRIs and Prefixes .......................................................................................22 1.3.5.1 IRIs ............................................................................................22
    [Show full text]
  • PDF Formats; the XHTML Version Has Active Links That You Can Follow
    Semantic Web @ W3C: Activities, Recommendations and State of Adoption Athens, GA, USA, 2006-11-09 Ivan Herman, W3C Ivan Herman, W3C RDF(S), tools We have a solid specification since 2004: well defined (formal) semantics, clear RDF/XML syntax Lots of tools are available. Are listed on W3C’s wiki: RDF programming environment for 14+ languages, including C, C++, Python, Java, Javascript, Ruby, PHP,… (no Cobol or Ada yet ) 13+ Triple Stores, ie, database systems to store datasets 16+ general development tools (specialized editors, application builders, …) etc Ivan Herman, W3C RDF(S), tools (cont.) Note the large number of large corporations among the tool developers: Adobe, IBM, Software AG, Oracle, HP, Northrop Grumman, … …but the small companies and independent developers also play a major role! Some of the tools are Open Source, some are not; some are very mature, some are not : it is the usual picture of software tools, nothing special any more! Anybody can start developing RDF-based applications today Ivan Herman, W3C RDF(S), tools (cont.) There are lots of tutorials, overviews, or books around the wiki page on books lists 20+ (English) textbooks; 19+ proceedings for 2005 & 2006 alone… again, some of them good, some of them bad, just as with any other areas… Active developers’ communities Ivan Herman, W3C Large datasets are accumulating IngentaConnect bibliographic metadata storage: over 200 million triplets UniProt Protein Database: 262 million triplets RDF version of Wikipedia: more than 47 million triplets RDFS/OWL Representation
    [Show full text]
  • Towards Unifying Rules and Policies for Semantic Web Services
    Towards Unifying Rules and Policies for Semantic Web Services Nima Kaviani 1, Dragan Gaševi ć1, Marek Hatala 1, David Clement 2, Gerd Wagner 3 1Simon Fraser University Surrey, Canada 2Visiphor Corporation, Canada 3Brandenburg University of Technology at Cottbus, Germany {nkaviani, dgasevic, mhatala}@sfu.ca, [email protected], [email protected] Abstract However, the current proposed standards for describing Semantic Web services (i.e. OWL-S [14], Simplifying the discovery of web services on one hand WSDL-S [1], Web Service Modeling Ontology [7], and protecting them from misuse on the other hand has and Semantic Web Service Language – SWSL [2]) initiated several lines of research in the area of policy- demonstrate that it is important to use a rule language aware semantic web services. However, the diversity of in addition to ontologies. This allows run-time approaches, ontologies and languages chosen for discovery, composition, and orchestration of Semantic defining Semantic Web services and policies has made Web services by defining preconditions or post- the research area cluttered. It is now ambiguous how conditions for all Web service messages exchanged different registries and agents with different policy [13]. For example, OWL-S recommends using OWL languages and Semantic Web service ontologies would ontologies together with different types of rule share their information. In this paper we try to solve languages (SWRL, KIF, or DRS), WSMO uses F- the problem of exchanging information between the Logic, while WSDL-S is fully agnostic about the use of registries by defining an interchange framework to a vocabulary (e.g., UML, ODM, OWL) or rule transform business rules and concepts from one language (e.g., OCL, SWRL, RuleML).
    [Show full text]
  • Enhancing JSON to RDF Data Conversion with Entity Type Recognition
    Enhancing JSON to RDF Data Conversion with Entity Type Recognition Fellipe Freire, Crishane Freire and Damires Souza Academic Unit of Informatics, Federal Institute of Education, Science and Technology of Paraiba, João Pessoa, Brazil Keywords: RDF Data Conversion, Entity Type Recognition, Semi-Structured Data, JSON Documents, Semantics Usage. Abstract: Nowadays, many Web data sources and APIs make their data available on the Web in semi-structured formats such as JSON. However, JSON data cannot be directly used in the Web of data, where principles such as URIs and semantically named links are essential. Thus it is necessary to convert JSON data into RDF data. To this end, we have to consider semantics in order to provide data reference according to domain vocabularies. To help matters, we present an approach which identifies JSON metadata, aligns them with domain vocabulary terms and converts data into RDF. In addition, along with the data conversion process, we provide the identification of the semantically most appropriate entity types to the JSON objects. We present the definitions underlying our approach and results obtained with the evaluation. 1 INTRODUCTION principles of this work is using semantics provided by the knowledge domain of the data to enhance The Web has evolved into an interactive information their conversion to RDF data. To this end, we use network, allowing users and applications to share recommended open vocabularies which are data on a massive scale. To help matters, the Linked composed by a set of terms, i.e., classes and Data principles define a set of practices for properties useful to describe specific types of things publishing structured data on the Web aiming to (LOV Documentation, 2016).
    [Show full text]
  • Linked Data Schemata: Fixing Unsound Foundations
    Linked data schemata: fixing unsound foundations. Kevin Feeney, Gavin Mendel Gleason, Rob Brennan Knowledge and Data Engineering Group & ADAPT Centre, School of Computer Science & Statistics, Trinity College Dublin, Ireland Abstract. This paper describes an analysis, and the tools and methods used to produce it, of the practical and logical implications of unifying common linked data vocabularies into a single logical model. In order to support any type of reasoning or even just simple type-checking, the vocabularies that are referenced by linked data statements need to be unified into a complete model wherever they reference or reuse terms that have been defined in other linked data vocabularies. Strong interdependencies between vocabularies are common and a large number of logical and practical problems make this unification inconsistent and messy. However, the situation is far from hopeless. We identify a minimal set of necessary fixes that can be carried out to make a large number of widely-deployed vocabularies mutually compatible, and a set of wider-ranging recommendations for linked data ontology design best practice to help alleviate the problem in future. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse in the wild. Keywords: Linked Data, Reasoning, Data Quality 1. Introduction One of the central tenets of the Linked Data movement is the reuse of terms from existing well- known vocabularies [Bizer09] when developing new schemata or datasets. The semantic web infrastructure, and the RDF, RDFS and OWL languages, support this with their inherently distributed and modular nature. In practice, through vocabulary reuse, linked data schemata adopt knowledge models that are based on multiple, independently devised ontologies that often exhibit varying definitional semantics [Hogan12].
    [Show full text]
  • Building Linked Data for Both Humans and Machines∗
    Building Linked Data For Both Humans and Machines∗ y z x Wolfgang Halb Yves Raimond Michael Hausenblas Institute of Information Centre for Digital Music Institute of Information Systems & Information London, UK Systems & Information Management Management Graz, Austria Graz, Austria ABSTRACT Existing linked datasets such as [3] are slanted towards ma- In this paper we describe our experience with building the chines as the consumer. Although there are exceptions to riese dataset, an interlinked, RDF-based version of the Eu- this machine-first approach (cf. [13]), we strongly believe rostat data, containing statistical data about the European that satisfying both humans and machines from a single Union. The riese dataset (http://riese.joanneum.at), aims source is a necessary path to follow. at serving roughly 3 billion RDF triples, along with mil- lions of high-quality interlinks. Our contribution is twofold: We subscribe to the view that every LOD dataset can be Firstly, we suggest using RDFa as the main deployment understood as a Semantic Web application. Every Semantic mechanism, hence serving both humans and machines to Web application in turn is a Web application in the sense effectively and efficiently explore and use the dataset. Sec- that it should support a certain task for a human user. With- ondly, we introduce a new way of enriching the dataset out offering a state-of-the-art Web user interface, potential with high-quality links: the User Contributed Interlinking, end-users are scared away. Hence a Semantic Web applica- a Wiki-style way of adding semantic links to data pages. tion needs to have a nice outfit, as well.
    [Show full text]
  • Linked Data Schemata: Fixing Unsound Foundations
    Linked data schemata: fixing unsound foundations Editor(s): Amrapali Zaveri, Stanford University, USA; Dimitris Kontokostas, Universität Leipzig, Germany; Sebastian Hellmann, Universität Leipzig, Germany; Jürgen Umbrich, Wirtschaftsuniversität Wien, Austria Solicited review(s): Mathieu d’Aquin, The Open University, UK; Peter F. Patel-Schneider, Nuance Communications, USA; John McCrae, Insight Centre for Data Analytics, Ireland; One anonymous reviewer Kevin Chekov Feeney, Gavin Mendel Gleason, and Rob Brennan Knowledge and Data Engineering Group & ADAPT Centre, School of Computer Science & Statistics, Trinity College Dublin, Ireland Corresponding author’s e-mail: [email protected] Abstract. This paper describes our tools and method for an evaluation of the practical and logical implications of combining common linked data vocabularies into a single local logical model for the purpose of reasoning or performing quality evalua- tions. These vocabularies need to be unified to form a combined model because they reference or reuse terms from other linked data vocabularies and thus the definitions of those terms must be imported. We found that strong interdependencies between vocabularies are common and that a significant number of logical and practical problems make this model unification inconsistent. In addition to identifying problems, this paper suggests a set of recommendations for linked data ontology design best practice. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse. Keywords: Linked Data, Reasoning, Data Quality 1. Introduction In order to validate any dataset which uses the adms:Asset term we must combine the adms ontolo- One of the central tenets of the linked data move- gy and the dcat ontology in order to ensure that ment is the reuse of terms from existing well-known dcat:Dataset is a valid class.
    [Show full text]
  • Slideshare.Net/Scorlosquet/Drupal-As-A-Semantic-Web-Platform
    Linked Data Publishing with Drupal Joachim Neubert ZBW – German National Library of Economics Leibniz Information Centre for Economics SWIB13 Workshop Hamburg, Germany 25.11.2013 ZBW is member of the Leibniz Association My background • Scientific software developer at ZBW – German National Library for Economics, mainly concerned with Linked Open Data and knowledge organization systems and services • Published 20th Century Press Archives in 2010, with some 100,000 digitized newspaper articles in dossiers (http://zbw.eu/beta/p20, custom application written in Perl) • Published a repository of ZBW Labs projects recently – basicly project descriptions and a blog (http://zbw.eu/labs, Drupal based) Page 2 Workshop Agenda – Part 1 1) Drupal 7 as a Content Management System: Linked Data by Default Hands-on: Get familiar with Drupal and it‘s default RDF mappings 2) Using Drupal 7as a Framework for Content Management Hands-on: Create a custom content type and map it to RDF Page 3 Workshop Agenda – Part 2 Produce other RDF Serialization Formats: RDF/XML, Turtle, Ntriples, JSON-LD Create a SPARQL Endpoint from your Drupal Site Cool URIs Create Out-Links with Web Taxonomy Current limitations of RDF/LD support in Drupal 7 Outlook on Drupal 8 Page 4 Drupal as a CMS (Content Management System) ready for RDF and Linked Data Page 5 Why at all linked data enhanced publishing? • Differentiate the subjects of your web pages and their attributes • Thus, foster data reuse in 3rd party services and applications • Mashups • Search engines • Create meaningful
    [Show full text]
  • A User-Friendly Interface to Browse and Find DOAP Projects with Doap:Store
    A user-friendly interface to browse and find DOAP projects with doap:store Alexandre Passant Universit´eParis IV Sorbonne, Laboratoire LaLICC, Paris, France [email protected] 1 Motivation The DOAP[2] vocabulary is now widely used by people - and organizations - to describe their projects using Semantic Web standards. Yet, since files are spread around the Web, there is no easy way to find a project regarding its metadata. Recently, Ping The Semantic Web1 (PTSW) and Semantic Radar2 plugin for Firefox introduced a new way to discover Semantic Web documents[1]: by brows- ing the Web, users ping the PTSW service so that it can maintain a contineously updated list of Semantic Web document URIs. Thus, the idea of doap:store - http://doapstore.org is to provide a user- friendly interface, easily accessible for not RDF-aware users, to find and browse DOAP projects, using PTSW as a provider of data sources. This way, users do not have to register to promote a project as in freshmeat3 or related services, but just need to publish some DOAP files on their websites to benefit of this distributed architecture. doap:store is the first implemented service using PTSW data sources to provide such browsing and querying features. 2 Architecture doap:store involves 3 main components: – A crawler: Running hourly, a tiny script parses the list of latest DOAP pings received by PTSW and then put each related RDF files into a triple-store; – A triple-store: The core of the system, storing RDF files retrieved thanks to the crawler, and providing SPARQL capabilities to be used by the user- interface that is plugged on the endpoint; – A user-interface: A simple interface, offering a list of latest retrieved projects, a case-insensitive tagcloud of programming languages, and a search engine to find DOAP projects regarding various criteria in a easy way.
    [Show full text]
  • Combining RDF Vocabularies for Expert Finding
    Combining RDF Vocabularies for Expert Finding Boanerges Aleman-Meza1, Uldis Boj¯ars2, Harold Boley3, John G. Breslin2, Malgorzata Mochol4, Lyndon JB Nixon4, Axel Polleres2,5, and Anna V. Zhdanova5 1 LSDIS Lab, University of Georgia, USA 2 DERI, National University of Ireland, Galway 3 University of New Brunswick and National Research Council, Canada 4 Free University of Berlin, Germany 5 Universidad Rey Juan Carlos, Madrid, Spain 6 University of Surrey, UK Abstract. This paper presents a framework for the reuse and extension of ex- isting, established vocabularies in the Semantic Web. Driven by the primary ap- plication of expert finding, we will explore the reuse of vocabularies that have attracted a considerable user community already (FOAF, SIOC, etc.) or are de- rived from de facto standards used in tools or industrial practice (such as vCard, iCal and Dublin Core). This focus guarantees direct applicability and low entry barriers, unlike when devising a new ontology from scratch. The Web is already populated with several vocabularies which complement each other (but also have considerable overlap) in that they cover a wide range of necessary features to adequately describe the expert finding domain. Little effort has been made so far to identify and compare existing approaches, and to devise best practices on how to use and extend various vocabularies conjointly. It is the goal of the re- cently started ExpertFinder initiative to fill this gap. In this paper we present the ExpertFinder framework for reuse and extension of existing vocabularies in the Semantic Web. We provide a practical analysis of overlaps and options for com- bined use and extensions of several existing vocabularies, as well as a proposal for applying rules and other enabling technologies to the expert finding task.
    [Show full text]
  • The RDF Layer
    Knowledge Representation and Semantic Technologies The RDF layer Riccardo Rosati Corso di Laurea Magistrale in Ingegneria Informatica Sapienza Università di Roma 2019/2020 The Semantic Web Tower The RDF layer 2 Syntax and semantics • Syntax: the structure of data • Semantics: the meaning of data • Two conditions necessary for interoperability: – Adopt a common syntax: this enables applications to parse the data. – Adopt a means for understanding the semantics: this enables applications to use the data. The RDF layer 3 XML • XML: eXtensible Mark-up Language • XML documents are written through a user- defined set of tags • tags are used to express the “semantics” of the various pieces of information The RDF layer 4 XML: example <course date=“2007”> <title>Seminari di Ingegneria del Software </title> <teacher> <name>Giuseppe De Giacomo</name> <email>[email protected]</email> </teacher> <prereq>none</prereq> </course> The RDF layer 5 XML • XML: document = labelled tree • node = label + attributes/values + contents <course date=“...”> <title>...</title> course <teacher> <office>...</office> <email>...</email> = title teacher prereq </teacher> <prereq>...</prereq> </course> office email The RDF layer 6 XML • XML Schema = grammar for describing legal trees and datatypes • can we use XML to represent semantics? The RDF layer 7 XML and semantics <Predator> … </Predator> • Predator: a medium-altitude, long-endurance unmanned aerial vehicle system. • Predator : one that victimizes, plunders, or destroys, especially for one's own gain. • Predator
    [Show full text]
  • Model Driven Architecture and Classification of Business Rules
    Proceedings of the Federated Conference on ISBN 978-83-60810-51-4 Computer Science and Information Systems pp. 949–952 Model Driven Architecture and classification of business rules modelling languages Bartłomiej Gaweł Iwona Skalna AGH University of Science and Technology AGH University of Science and Technology in Krakow in Krakow ul.Gramatyka 10, 30-067 Krakow, Poland ul.Gramatyka 10, 30-067 Krakow, Poland Email: [email protected] Email: [email protected] Abstract—An organisation’s activity under dynamic changes of II. BUSINESS RULES AND SEMANTICS WEB business processes requires continuous improvement of business practices. This implies the necessity of refining decision making The definition of a business rule, coming from GUIDE process. Business rules [6], [8] enable experts to transfer enter- [11], states that a business rule is "a statement that defines or prise strategy onto the operational level using simple sentences constraints some aspect of the business. It is intended to assert which, in turn, can automate reactions to subsequent events both business structure or to control or influence the behaviour of inside and outside the organisation. The main advantage of the the business." In [10], Ross describes several basic principles business rules is their simplicity and flexibility so they can be easily utilised by different organisations for different purposes. of business rules approach. He believes that a language has In order to represent knowledge in a pseudo-natural language the biggest impact on business rules expressiveness. Therefore, understandable to information systems (business rules engines) in the remaining part of this study business rules description notation and description standards are required.
    [Show full text]