Survey of Cardinality Constraints in Snapshot and Temporal Semantic Data Models

2010 ◽  
pp. 25-41
Author(s):  
Faiz Currim ◽  
Sudha Ram
Keyword(s):  
Conceptual Modeling ◽  
Past Research ◽  
Schema Integration ◽  
Cardinality Constraints ◽  
Semantic Data ◽  
Query Transformation ◽  
Temporal Domain ◽  
Conceptual Modeling Grammar ◽  
Conceptual Data ◽  
Future Work

Cardinality captures necessary semantics in conceptual data modeling and determines how constructs are translated into relations. Business policies in a variety of domains like healthcare, education, supply chain management and geographic systems are often expressible in terms of cardinality. The knowledge about cardinality constraints is also useful during schema integration, in query transformation for more efficient search strategies, and in database testing. Practically every conceptual modeling grammar provides support for this kind of constraint, and in an effort to resolve the variations in semantics past research has studied the different types of cardinality constraints. None have been so far comprehensive, and further there has been very little coverage of the concept in temporal domain even though it provides some interesting extensions to the concept. This study considers existing work in snapshot and temporal cardinality and suggests some areas for future work.

Using Ontology Languages for Conceptual Modeling

2012 ◽  
pp. 1-28
Author(s):  
Palash Bera ◽  
Anna Krasnoperova ◽  
Yair Wand
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Systems Development ◽  
Information Systems Development ◽  
Semantic Relationships ◽  
Support Domain ◽  
Domain Semantics ◽  
Ontology Languages ◽  
Conceptual Modeling Grammar ◽  
Precise Representation

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

CoolWikNews

2011 ◽  
pp. 69-83
Author(s):  
Damaris Fuentes-Lorenzo ◽  
Juan Miguel Gómez ◽  
Ángel García Crespo
Keyword(s):  
Semantic Data ◽  
Semantic Wiki ◽  
Future Work

This chapter deals with a semantic wiki application devoted to news publishing, Cool- WikNews. This semantic application offers the functionalities of a traditional wiki, but enhanced with semantic data. It focuses on the simplicity of both use and browsing, the accurate retrieval of information, and its flexibility to be applied in any domain apart from news publishing. In this chapter, definitions related with this topic will be explained, apart from describing the steps taken so far and the problems still to overcome. Inwards and advantages of CoolWikNews will be presented, paying more attention in how this application overcomes the problems arisen. The chapter concludes with future work and several remarks.

An Enterprise Ontology Based Conceptual Modeling Grammar for Representing Value Chain and Supply Chain Scripts

2016 ◽  
pp. 119-137
Author(s):  
Wim Laurier ◽  
Geert Poels
Keyword(s):  
Supply Chain ◽  
Value Chain ◽  
Conceptual Modeling ◽  
Third Party ◽  
Agent Model ◽  
Business Modeling ◽  
Business Partners ◽  
System Interoperability ◽  
Conceptual Modeling Grammar ◽  
Enterprise Ontology

In business modeling the focus is shifting from individual enterprises to the supply chains in which they collaborate. Contemporary business modeling grammars should allow each enterprise taking part in a supply chain to develop its own information system and at the same time support the creation of system interoperability and information sharing amongst business partners in the supply chain. This paper presents a conceptual modeling grammar for representing business scripts in a way that is both observer-dependent and independent. That is, value chain information should be represented in a format that is suitable for the perspective of any partner in the supply chain (e.g., enterprise, supplier, customer, customer's customer, supplier's supplier) and for the perspective of a completely neutral third party (e.g., government). The proposed observer-independent conceptual-modeling grammar, which is given strength by grounding it in the mature Resource-Event-Agent model, is shown to represent information about business phenomena of diverse supply chain partners such that it can be integrated across enterprise boundaries

Semantics of the MibML Conceptual Modeling Grammar

2007 ◽  
Vol 18 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Hong Zhang ◽  
Rajiv Kishore ◽  
Ram Ramesh
Keyword(s):  
Conceptual Modeling ◽  
Conceptual Modeling Grammar

Semantic Data Mapping on E-Learning Usage Index Tool to Handle Heterogeneity of Data Representation

2014 ◽  
Vol 69 (5) ◽  
Author(s):  
Arda Yunianta ◽  
Norazah Yusof ◽  
Mohd Shahizan Othman ◽  
Abdul Aziz ◽  
Nataniel Dengen ◽  
...  
Keyword(s):  
Data Representation ◽  
Current Data ◽  
Data Mapping ◽  
Semantic Technology ◽  
Semantic Data ◽  
Triple Store ◽  
Integration Problem ◽  
E Learning ◽  
Semantic Ontology ◽  
Future Work

Distribution and heterogeneity of data is the current issues in data level implementation. Different data representation between applications makes the integration problem increasingly complex. Stored data between applications sometimes have similar meaning, but because of the differences in data representation, the application cannot be integrated with the other applications. Many researchers found that the semantic technology is the best way to resolve the current data integration issues. Semantic technology can handle heterogeneity of data; data with different representations and sources. With semantic technology data mapping can also be done from different database and different data format that have the same meaning data. This paper focuses on the semantic data mapping using semantic ontology approach. In the first level of process, semantic data mapping engine will produce data mapping language with turtle (.ttl) file format that can be used for Local Java Application using Jena Library and Triple Store. In the second level process, D2R Server that can be access from outside environment is provided using HTTP Protocol to access using SPARQL Clients, Linked Data Clients (RDF Formats) and HTML Browser. Future work to will continue on this topic, focusing on E-Learning Usage Index Tool (IPEL) application that is able to integrate with others system applications like Moodle E-Learning Systems. 

Q-Bot, the Quarantine Robot: Joint-media engagement between children and adults about quarantine living experiences

2020 ◽  
Vol 121 (5/6) ◽  
pp. 401-409
Author(s):  
Sonia Tiwari
Keyword(s):  
Design Methodology ◽  
Secondary Data ◽  
Past Research ◽  
Content Type ◽  
Media Design ◽  
Hygiene Practices ◽  
Cdc Guidelines ◽  
Open Coding ◽  
Future Work ◽  
Practical Implications

Purpose Information about the COVID-19 pandemic and quarantine can be challenging to communicate to children. The purpose of this study is to understand how a children’s eBook can help facilitate conversations between children, families and educators about the pandemic. Design/methodology/approach A children’s eBook Q-Bot: The Quarantine Robot was shared by the researcher with parents and teachers through social media (Facebook, Instagram and Twitter). The story provides information (based on CDC guidelines) on the best health and hygiene practices to avoid catching the virus, while also drawing attention to the hardworking people who are helping us through this experience. Data was collected as public comments on the eBook. Secondary data included other children’s eBooks available on the same theme and their public reviews. Findings Through open coding of comments, the researcher found that the children’s eBook helped in facilitation of discussion between children, parents and teachers; around the pandemic’s effects on health and hygiene practices; and remote learning experiences. A content analysis of other children’s books on this theme revealed a set of guidelines for designing helpful eBooks for pandemic quarantine situations in general. Research limitations/implications Education, media and health researchers may find this study helpful in understanding the potential of children’s eBooks as probes, prompts or communication tools. Practical implications Experts in pandemic-related issues, educators, illustrators and authors may find this study helpful in understanding guidelines for creating educational children’s eBooks for similar situations in the future. Originality/value Both theoretical and practical values are addressed through this study, as it provides helpful literature from past research, offers new insights from current study and guidelines for future work in narrative media design for the pandemic and other similar situations.

A Framework for Ontology-Based Heterogeneous Data Integration for Cost Management in Product Family Design

2008 ◽  
Author(s):  
Xiaomeng Chang ◽  
Janis Terpenny
Keyword(s):  
Product Family ◽  
Heterogeneous Data ◽  
Schema Integration ◽  
Product Family Design ◽  
Related Factors ◽  
Product Families ◽  
Heterogeneous Data Integration ◽  
Related Information ◽  
Semantic Data ◽  
Data Schema

High quality, high impact and economical products and systems are important goals for an enterprise. The usage of product families can be strategic to achieving these goals, yet defining these families can be challenging, requiring the consideration of numerous cost factors. This requires bringing together a great number of heterogeneous data sources of varying formats in a manner that allows the product development team to easily locate and reuse information in a collaborative manner across time and space. To date, our work has focused on the development and use of an Activity-Based Cost ontology (ABC ontology) to guide designers drill down to get at information for product family design. However, this ontology is built in such a way that it can only support information retrieval from the ontology and does not bring together and connect heterogeneous data resources. It does not address the problem of designers who struggle with obtaining relevant details from different departments in an enterprise. While there have been several semantic data schema integration tools for heterogeneous data resources integration, these tools cannot guide users to related information, that would lead to the root cause of the high cost. In this paper, in order to better manage cost in product family design, an ontology-based framework is put forward that builds on our prior work and combines the advantages of ABC ontology and data schema integration tools. The ontology-based framework can guide users to the proper information aspects through querying the central ontology, and give users detailed information about these aspects from heterogeneous data resources with the support of local ontologies. Ultimately, this framework will facilitate designers with better utilization of cost-related factors for product family design from a whole enterprise perspective.

Using Ontology Languages for Conceptual Modeling

2010 ◽  
Vol 21 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Palash Bera ◽  
Anna Krasnoperova ◽  
Yair Wand
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Information Systems Development ◽  
Semantic Relationships ◽  
Modeling Techniques ◽  
Support Domain ◽  
Domain Semantics ◽  
Ontology Languages ◽  
Conceptual Modeling Grammar ◽  
Precise Representation

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

scholarly journals Implementing E-Learning Ontology to Scale For Provenance

2019 ◽  
Vol 8 (9) ◽  
pp. 670-675
Keyword(s):  
Semantic Web ◽  
Learning Model ◽  
Model Data ◽  
Web Based ◽  
Semantic Data ◽  
Web Based Learning ◽  
Proposed Model ◽  
E Learning ◽  
Academic Resource ◽  
Future Work

This paper explores the aspects of providing education through E-learning model evaluating its relevance to distance education and for ICT systems. A subset of E-learning is a Web based learning that makes the learning -easier, impressive, structured and properly managed. The paper defines an university ontology describing how e-learning provides resources which are available online and designated cloud that can be delivered anywhere any time among the users. In the proposed model data is stored in designated cloud and users are able to share efficiently the same as it provides services to learner. Provenance or trust with respect to the academic resource is a major concern in these types of models, users accessing data must be trustable which help learners, researchers, developers, and users in future work also. This paper proposes an e-learning model which is well organized and structured, such that the machine responds with the accurate, trustable, desired information and results. The paper defines an ontology for semantic structuring, semantic rendering and applies provenance on suggested ontology to achieve authentic results. It is also desired to establish trust of the source contents of the Semantic Web, with the result that a user receiving data will need to verify whether the received data from source is in fact trustable or not. The defined ontogoly is suitable for consumption of both man and machine in the context of the e-learning and Semantic data rendering Web Keywords

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