1,721,049 research outputs found
Issues and Guidelines in Modeling Decomposition of Minimum Participation in Entity-Relationship Diagrams
Full text linkThe entity-relationship model has long been employed for conceptual modeling of databases. Methodologies and heuristics have been developed, both for effective modeling and for translating entity-relationship models into relational models. One aspect of modeling that is often overlooked in design methodologies is the use of optional versus mandatory participation (i.e., minimum participation) on the development of relational databases. This tutorial complements existing instructional material on database design by analyzing the syntactic implications of minimum participation in binary, unary, and n-ary relationship sets and for the special case where the E-R diagram depicts a database where 3NF is not in BCNF. It then presents design modeling guidelines which demonstrate that (1) for binary 1:1 and 1:M relationship sets, the presence of optional participation sometimes means that the relationship set should be represented in the relational model by a separate relation, (2) unary relationship sets cannot have a (1,1) participation, (3) n-ary relationship sets that have a (1,1) participation can be simplified to be of lower connectivity, and (4) decomposition is not a substitute for normalization. Illustrative examples and modeling guidelines are provided.Originally published in:
Chua, Cecil and Storey, Veda C. (2011) "Issues and Guidelines in Modeling Decomposition of Minimum Participation in Entity-Relationship Diagrams," Communications of the Association for Information Systems: Vol. 29, Article 9. Available at: http://aisel.aisnet.org/cais/vol29/iss1/9
Posted with the permission of the publisher.</p
Semantic interoperability: ontological unpacking of a viral conceptual model
Full text linkBackground. Genomics and virology are unquestionably important, but complex, domains being investigated by a large number of scientists. The need to facilitate and support work within these domains requires sharing of databases, although it is often difficult to do so because of the different ways in which data is represented across the databases. To foster semantic interoperability, models are needed that provide a deep understanding and interpretation of the concepts in a domain, so that the data can be consistently interpreted among researchers.
Results. In this research, we propose the use of conceptual models to support semantic interoperability among databases and assess their ontological clarity to support their effective use. This modeling effort is illustrated by its application to the Viral Conceptual Model (VCM) that captures and represents the sequencing of viruses, inspired by the need to understand the genomic aspects of the virus responsible for COVID-19. For achieving semantic clarity on the VCM, we leverage the “ontological unpacking” method, a process of ontological analysis that reveals the ontological foundation of the information that is represented in a conceptual model. This is accomplished by applying the stereotypes of the OntoUML ontology-driven conceptual modeling language.As a result, we propose a new OntoVCM, an ontologically grounded model, based on the initial VCM, but with guaranteed interoperability among the data sources that employ it.
Conclusions. We propose and illustrate how the unpacking of the Viral Conceptual Model resolves several issues related to semantic interoperability, the importance of which is recognized by the “I” in FAIR principles. The research addresses conceptual uncertainty within the domain of SARS-CoV-2 data and knowledge.The method employed provides the basis for further analyses of complex models currently used in life science applications, but lacking ontological grounding, subsequently hindering the interoperability needed for scientists to progress their research
An Ontological Characterization of a Conceptual Model of the Human Genome
Full text linkThe ability to sequence the human genome is a scientific, historical breakthrough. Although the human genome mapping is available to all scientists, information about it can be difficult to share. The Conceptual Schema of the Human Genome represents the concepts required to holistically understand the human genome. We report on our continued efforts to ensure that the human genome can be meaningfully shared by conducting an ontological analysis and enrichment of the conceptual model to facilitate domain understanding and data exchange among heterogeneous systems. The analysis and enrichment process is supported by the ontology-driven conceptual modeling language, OntoUML, to gain ontological clarity and demonstrated on a relevant section of the Pathways view of the schema. Consistent with the overall objective of designing a sound genomics information system, the results lead to major modeling implications for the: characterization of biological entities; changes in biological entities over time; and representation of chemical compounds. Our research shows that the inclusion of a strong ontological foundation in a conceptual model contributes to the design of complex systems
An Initial Empirical Assessment of an Ontological Model of the Human Genome
Full text linkConceptual modeling is used to model application domains for which an information system is needed. One of the most complex domains to which conceptual modeling has been applied is that of the human genome. Due to its complexity, its understanding is often left to domain experts. Conceptual models represent genomics-related concepts, with various purposes, including domain clarification or data structures design for facilitating data integration. However, traditional conceptual models, which might be expressed, for example, with UML, may not be appropriate for properly explaining such a complex domain, thus requiring an additional layer to ground the model on well-accepted ontological foundations. To achieve this result, an “ontological unpacking” method has been proposed that uses OntoUML as a visual formalism. In this research, we carry out an empirical study to compare the two mentioned representations. The study involved a small group of participants, who responded to a set of questions by reading either a UML model or its related OntoUML unpacked version; the results enabled us to assess their understanding of the domain. We aim to initiate a practical evaluation framework to assess the effectiveness, efficiency and user beliefs of models derived by ontologically unpacking traditional conceptual models. The results of the analysis provide the basis for a broader assessment
The Sciences of Design: Observations on an Emerging Field
No full textThe boundaries and contours of design sciences continue to undergo definition and refinement. In many ways, the sciences of design defy disciplinary characterization. They demand multiple epistemologies, theoretical orientations (e.g. construction, analysis or intervention) and value considerations. As our understanding of this emerging field of study grows, we become aware that the sciences of design require a systemic perspective that spans disciplinary boundaries. The Doctoral Consortium at the Design Science Research Conference in Information Sciences and Technology (DESRIST) was an important milepost in their evolution. It provided a forum where students and leading researchers in the design sciences challenged one another to tackle topics and concerns that are similar across different disciplines. This paper reports on the consortium outcomes and insights from mentors who took part in it. We develop a set of observations to guide the evolution of the sciences of design. It is our intent that the observations will be beneficial, not only for IS researchers, but also for colleagues in allied disciplines who are already contributing to shaping the sciences of design.Originally published in:
Purao, Sandeep; Baldwin, Carliss; Hevner, Alan; Storey, Veda C.; Pries-Heje, Jan; Smith, Brian; and Zhu, Ying (2008) "The Sciences of Design: Observations on an Emerging Field,"Communications of the Association for Information Systems: Vol. 23, Article 29. Available at: http://aisel.aisnet.org/cais/vol23/iss1/29
Posted with the permission of the publisher.</p
Ontological Distinctions between Means-End and Contribution Links in the i* Framework
Full text linkThe i* framework is a renowned Requirements Engineering approach. This work is part of an ongoing effort to provide ontological interpretations for the i* core concepts. With this, we aim at proposing a more uniform use of the language, in a way that it can be more easily learned by newcomers and more efficiently transferred to industry. Our approach is based on the application of a foundational ontology named UFO, which is used as a semantically coherent reference model to which the language should be isomorphic. In this paper, we focus on the Means-end and the Contribution links. We aim at presenting the community with some possible ontological interpretations of these links, aiming at promoting constructive debate and receiving feedback about the validity of our assumptions
Using unified modeling language for conceptual modelling of knowledge-based systems
No full textThis paper discusses extending the Unified Modelling Language by means of a profile for modelling knowledge-based system in the context of Model Driven Architecture (MDA) framework. The profile is implemented using the eXecutable Modelling Framework (XMF) Mosaic tool.A case study from the health care domain demonstrates the practical use of this profile; with the prototype implemented in Java Expert System Shell (Jess).The paper also discusses the possible mapping of the profile elements to the platform specific model (PSM) of Jess and provides some discussion on the Production Rule Representation (PRR) standardisation work
Ontology-driven business modelling: improving the conceptual representation of the REA ontology
No full textBusiness modelling research is increasingly interested in exploring how domain ontologies can be used as reference models for business models. The Resource Event Agent (REA) ontology is a primary candidate for ontology-driven modelling of business processes because the REA point of view on business reality is close to the conceptual modelling perspective on business models. In this paper Ontology Engineering principles are employed to reengineer REA in order to make it more suitable for ontology-driven business modelling. The new conceptual representation of REA that we propose uses a single representation formalism, includes a more complete domain axiomatization (containing definitions of concepts, concept relations and ontological axioms), and is proposed as a generic model that can be instantiated to create valid business models. The effects of these proposed improvements on REA-driven business modelling are demonstrated using a business modelling example
On the symbiosis between enterprise modelling and ontology engineering
No full textIn different fields, ontologies are increasingly deployed to specify and fix the terminology of a particular domain. In enterprise modelling, their main use lies in serving as a knowledge base for enterprise model creation. Such models, based on one or several compatible so-called enterprise-specific ontologies, allow for model alignment and solve interoperability issues. On the other hand, enterprise models may enrich the enterprise-specific ontology with concepts emerging from practical needs. In order to achieve this reciprocal advantage, we developed an ontology-based enterprise modeling meta-method that facilitates modelers to construct their models using the enterprise-specific ontology. While doing so, modelers give their feedback for ontology improvement. This feedback is subject to community approval, after which it is possibly incorporated into the ontology, thereby evolving the ontology to better fit the enterprise’s needs
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