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11th International-Business-Information-Management-Association Conference

作者： Paiano, Roberto Guido, Anna Lisa Salento Univ Engn Innovat Dept Lecce Italy

ISBN: (纸本)9780982148907

The information has always been a valuable patrimony for the information systems that every company tries to capitalize as much as possible. With the web, the amount of information is increased and several problems arise for instance for the safety of the exchanged data but also to the semantic heterogeneity: the same information is very often represented in different ways in different information systems. In this paper we present an architecture of interchange of data both within the sate information system and among different information systems founded on the ontologies in order to overcome the problem list of the heterogeneity. Ontologies, today, they seem to be the best tool useful to resolve the problem of heterogeneity, but that has not now been exploited fully.

关键词： semantic data integration Information Systems Ontology data interchange

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Using semantic data integration to create reliable rule-based systems with uncertainty

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2011年第8期24卷 1499-1509页

作者： Jankowska, Beata Poznan Univ Tech Inst Control & Informat Engn PL-60965 Poznan Poland

An expert system is considered to be reliable if it generates reliable hypotheses. The quality of the hypotheses depends mainly on the effectiveness of system's knowledge base. This paper discusses the problem of designing effective knowledge bases for rule-based systems with uncertainty. The knowledge is acquired from aggregate data stored in various repositories. The data can differ, to some extent, both in syntax and in semantics. The first part of an algorithm for rules' generation and refinement operates by means of semantic data integration. It allows to join aggregate data from different repositories and generate strong production rules. The second part of the algorithm is based on a formal concept of the normal base form. For having the property of normality, a knowledge base has to be internally consistent and not redundant. In the process of rules' refinement, the rules violating the normality are eliminated. The effectiveness of the obtained knowledge base, dependent on the base's size and on rules' reliabilities, is high. The considerations are illustrated with medical examples. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： semantic data integration Ruled-based system Uncertainty Knowledge base Quality metric

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SNOWL model: social networks unification-based semantic data integration

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KNOWLEDGE AND INFORMATION SYSTEMS 2020年第11期62卷 4297-4336页

作者： Sebei, Hiba Hadj Taieb, Mohamed Ali Ben Aouicha, Mohamed Multimedia InfoRmat Syst & Adv Comp Lab Sfax Tunisia Univ Sfax Dept Comp Sci Fac Sci Sfax Tunisia

Integrating social networks data in the process of promoting business and marketing applications is widely addressed by several researchers. However, regarding the isolation between social network platforms managing such data has become a challenging task facing data scientist. In this respect, the present paper is designed to put forward a special semantic data integration approach, whereby a unified presentation and access to social networks data can be maintained. To this end, the novel SNOWL (Social Network OWL) ontology aims to provide a new social network content modeling, following the UPON Lite ontology-construction methodology. The advanced ontology is not created from scratch;it is but a continuation of some previously devised ontologies, elaborated to integrate an additional selection of newly incorporated social entities, such as content and user popularity. Additionally, and for an effective advantage of the model to be gained, a special mapping of the social networks data has been firstly implemented to the designed ontology, developed on the basis of the RML mapping language. Secondly, the SNOWL ontology is evaluated through the OOPS! Pitfall tool. Finally, a set of SPARQL-based services has also been designed on top of the SNOWL ontology in a bid to ensure a unified access to the mapped social data.

关键词： Social networks semantic data integration Knowledge discovery SPARQL query RML

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An ontology-guided semantic data integration framework to support integrative data analysis of cancer survival

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BMC MEDICAL INFORMATICS AND DECISION MAKING 2018年第2期18卷 129-147页

作者： Zhang, Hansi Guo, Yi Li, Qian George, Thomas J. Shenkman, Elizabeth Modave, Francois Bian, Jiang Univ Florida Coll Med Dept Hlth Outcomes & Biomed Informat Clin & Translat Res Bldg Suite 32282004 Mowry Rd Gainesville FL 32610 USA Univ Florida Coll Med Dept Med Div Hematol & Oncol Gainesville FL USA

Background: Cancer is the second leading cause of death in the United States, exceeded only by heart disease. Extant cancer survival analyses have primarily focused on individual-level factors due to limited data availability from a single data source. There is a need to integrate data from different sources to simultaneously study as much risk factors as possible. Thus, we proposed an ontology-based approach to integrate heterogeneous datasets addressing key data integration challenges. Methods: Following best practices in ontology engineering, we created the Ontology for Cancer Research Variables (OCRV) adapting existing semantic resources such as the National Cancer Institute (NCI) Thesaurus. Using the global-as-view data integration approach, we created mapping axioms to link the data elements in different sources to OCRV. Implemented upon the Ontop platform, we built a data integration pipeline to query, extract, and transform data in relational databases using semantic queries into a pooled dataset according to the downstream multi-level Integrative data Analysis (IDA) needs. Results: Based on our use cases in the cancer survival IDA, we created tailored ontological structures in OCRV to facilitate the data integration tasks. Specifically, we created a flexible framework addressing key integration challenges: (1) using a shared, controlled vocabulary to make data understandable to both human and computers, (2) explicitly modeling the semantic relationships makes it possible to compute and reason with the data, (3) linking patients to contextual and environmental factors through geographic variables, (4) being able to document the data manipulation and integration processes clearly in the ontologies. Conclusions: Using an ontology-based data integration approach not only standardizes the definitions of data variables through a common, controlled vocabulary, but also makes the semantic relationships among variables from different sources explicit and clear to al

关键词： semantic data integration Ontology semantic web Cancer survival Integrative data analysis

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Some Notes on Declarative Specification of semantic data integration Task in a Peer-to-peer Agent System

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NEW GENERATION COMPUTING 2010年第1期28卷 95-109页

作者： Brzykcy, Grazyna Poznan Univ Tech Inst Control & Informat Engn PL-60965 Poznan Poland

In the paper, a problem of semantic integration of XML data in a peer-to-peer agent system is analysed upon a channel theory. In the system, each agent manages its local data, and communication and cooperation actions, executed by the agents, consist of asking and answering queries. The abstract notions of classification and infomorphism are used to clarify the roles of queries and mappings in the system. The query reformulation task is modelled by the composition of an appropriate infomorphisms. In order to specify classifications and infomorphisms executable Prolog-like clauses and generelized terms are used. Logic programming systems are chosen because of the logical variables and partial data representation, effective techniques of data unification and partial evaluation, suitable built-in terms and procedures, and automated reasoning.

关键词： Declarative Specification semantic data integration Peer-to-peer System XML data Schema Mapping Query Rewriting Information Flow Channel Theory

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Towards a conceptual framework for African smart cities semantic data integration 5

Towards a conceptual framework for African smart cities sema...

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5th IEEE Annual International Smart Cities Conference (ISC2)

作者： Guinko, Ferdinand Traore, Yaya Ben Sta, Hatem Univ Joseph KI ZERBO Comp Sci Dept Inst Burkinabe Arts & Metiers Ouagadougou Burkina Faso Univ El Manar Comp Sci Dept Tunis Tunisia

ISBN: (纸本)9781728108469

Smart cities are composed of a number of dimensions such as transportation system, education system, health system, governance system, etc., that generate great amount of data that are stored such as heap of data. But these heap of data remain independent one from another. In this paper, we have presented a conceptual framework for a smart city semantic data integration.

关键词： African cities semantic data integration Internet of Things (IoT) Smart Cities Africa Smart mobility Burkinabe cities Internet of Things (IoT) Smart Cities

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MapSDI: A Scaled-Up semantic data integration Framework for Knowledge Graph Creation

MapSDI: A Scaled-Up Semantic Data Integration Framework for ...

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27th International Conference on Cooperative Information Systems, (CoopIS) / International Conference on Ontologies, databases, and Applications of semantics (ODBASE) / Conference on Cloud and Trusted Computing (C and TC)

作者： Jozashoori, Samaneh Vidal, Maria-Esther Leibniz Univ Hannover L3S Res Ctr Hannover Germany TIB Leibniz Informat Ctr Sci & Technol Hannover Germany

ISBN: (纸本)9783030332464;9783030332457

semantic web technologies have significantly contributed with effective solutions for the problems of data integration and knowledge graph creation. However, with the rapid growth of big data in diverse domains, different interoperability issues still demand to be addressed, being scalability one of the main challenges. In this paper, we address the problem of knowledge graph creation at scale and provide MapSDI, a mapping rule-based framework for optimizing semantic data integration into knowledge graphs. MapSDI allows for the semantic enrichment of large-sized, heterogeneous, and potentially low-quality data efficiently. The input of MapSDI is a set of data sources and mapping rules being generated by a mapping language such as RML. First, MapSDI pre-processes the sources based on semantic information extracted from mapping rules, by performing basic database operators;it projects out required attributes, eliminates duplicates, and selects relevant entries. All these operators are defined based on the knowledge encoded by the mapping rules which will be then used by the semantification engine (or RDFizer) to produce a knowledge graph. We have empirically studied the impact of MapSDI on existing RDFizers, and observed that knowledge graph creation time can be reduced on average in one order of magnitude. It is also shown, theoretically, that the sources and rules transformations provided by MapSDI are data-lossless.

关键词： Knowledge graph creation semantic data integration Transformation rules data integration system

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IoT semantic data integration through Ontologies

IoT Semantic Data Integration through Ontologies

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IEEE International Conference on Services Computing (IEEE SCC)

作者： Teniente, Ernest Univ Politecn Catalunya UPC Barcelona Catalonia Spain

ISBN: (数字)9781665481465

ISBN: (纸本)9781665481465

In this position statement we advocate how the use of ontologies may provide a proper solution for IoT semantic data integration. With this, we will improve IoT interoperability and will facilitate the development of software applications that allow providing management and monitoring of different IoT installations in a generic and homogeneous way.

关键词： IoT semantic data integration ontology

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Efficient Monitoring of Multi-Disciplinary Engineering Constraints with semantic data integration in the Multi-Model Dashboard Process 19

Efficient Monitoring of Multi-Disciplinary Engineering Const...

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19th IEEE International Conference on Emerging Technology and Factory Automation (ETFA)

作者： Biffl, Stefan Winkler, Dietmar Mordinyi, Richard Scheiber, Stefan Holl, Gerald Vienna Univ Technol Inst Software Technol & Interact Syst CDL Flex A-1040 Vienna Austria Johannes Kepler Univ Linz CDL Automated Software Engn A-4040 Linz Austria

ISBN: (纸本)9781479948451

In a multi-disciplinary engineering project, such as the parallel engineering of industrial production plants, domain experts want to efficiently monitor project-level constraints that depend on technical parameter values in local engineering models. However, the heterogeneous representations of constraint parameters in these engineering models make the automation of constraint monitoring difficult. In this paper, we introduce the Multi-Model Dashboard (MMD) process providing semantically integrated values of parameters and of constraints to domain experts, as parameter values in various local models change during the project. The tool-supported MMD process guides the definition and monitoring of MMD parameters and constraints. We evaluate the effectiveness and efficiency of the MMD process in a feasibility study with requirements and data from real-world use cases at industry partners. Major results are that the MMD process was effective and efficient in eliciting relevant project constraints and model dependencies and in providing data for change impact analysis.

关键词： Software Engineering Methods in Automation semantic data integration Change Impact Analysis Engineering Process Observation

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4D-SETL A semantic data integration Framework 18

4D-SETL <i>A Semantic Data Integration Framework</i>

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18th International Conference on Enterprise Information Systems (ICEIS)

作者： de Cesare, Sergio Foy, George Lycett, Mark Brunel Univ London Coll Business Arts & Social Sci Uxbridge Middx England Brunel Univ London Coll Engn Design & Phys Sci Uxbridge Middx England

ISBN: (纸本)9789897581878

Although successfully employed as the foundation for a number of large-scale government and energy industry projects, foundational ontologies have not been widely adopted within mainstream Enterprise Systems (ES) data integration practice. However, as the closed-worlds of ES are opened to Internet scale data sources, there is an emerging need to better understand the semantics of such data and how they can be integrated. Foundational ontologies can help establish this understanding and therefore, there is a need to investigate how such ontologies can be applied to underpin practical ES integration solutions. This paper describes research undertaken to assess the effectiveness of such an approach through the development and application of the 4D-semantic Extract Transform Load (4D-SETL) framework. 4D-SETL was employed to integrate a number of large scale datasets and to persist the resultant ontology within a prototype warehouse based on a graph database. The advantages of the approach included the ability to combine foundational, domain and instance level ontological objects within a single coherent system. Furthermore, the approach provided a clear means of establishing and maintaining the identity of domain objects as their constituent spatiotemporal parts unfolded over time, enabling process and static data to be combined within a single model.

关键词： Foundational Ontology Perdurantist 4D semantic data integration Modelling Graph databases integration Frameworks

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