28,686 research outputs found

    Managing data through the lens of an ontology

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    Ontology-based data management aims at managing data through the lens of an ontology, that is, a conceptual representation of the domain of interest in the underlying information system. This new paradigm provides several interesting features, many of which have already been proved effective in managing complex information systems. This article introduces the notion of ontology-based data management, illustrating the main ideas underlying the paradigm, and pointing out the importance of knowledge representation and automated reasoning for addressing the technical challenges it introduces

    Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

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    The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

    Cloud migration of legacy applications

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    Factors shaping the evolution of electronic documentation systems

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    The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

    Automated analysis of feature models: Quo vadis?

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    Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186

    Tracing the Scenarios in Scenario-Based Product Design: a study to support scenario generation

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    Scenario-based design originates from the human-computer interaction and\ud software engineering disciplines, and continues to be adapted for product development. Product development differs from software development in the former’s more varied context of use, broader characteristics of users and more tangible solutions. The possible use of scenarios in product design is therefore broader and more challenging. Existing design methods that involve scenarios can be employed in many different stages of the product design process. However, there is no proficient overview that discusses a\ud scenario-based product design process in its full extent. The purposes of creating scenarios and the evolution of scenarios from their original design data are often not obvious, although the results from using scenarios are clearly visible. Therefore, this paper proposes to classify possible scenario uses with their purpose, characteristics and supporting design methods. The classification makes explicit different types of scenarios and their relation to one another. Furthermore, novel scenario uses can be referred or added to the classification to develop it in parallel with the scenario-based design\ud practice. Eventually, a scenario-based product design process could take inspiration for creating scenarios from the classification because it provides detailed characteristics of the scenario

    Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

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    The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

    Exploring a framework for advanced electronic business transactions

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    With the emergence of service-oriented computing technology, companies embrace new ways of carrying out business transactions electronically. Since the parties involved in an electronic business transaction (eBT) manage a heterogeneous information-systems infrastructure within their organizational domains, the collaboration complexity is considerable and safeguarding an interorganizational collaboration with an eBT is difficult, but of high significance. This paper describes a conceptual framework that pays attention to the complexities of an eBT and its differentiating characteristics that go further than traditional database transactions. Since the eBT is a framework that comprises separate levels, pre-existing transaction concepts are explored for populating the respective levels. To show the feasibility of the described eBT framework, industry initiatives that are aspiring to become business-transaction standards, are checked for eBT compatible characteristics. Since realizing an eBT framework raises many tricky issues, the paper maps out important research areas that require scientific attention. Essentially, it is required to investigate how the business semantics influences the nature of an eBT throughout its lifecycle.Peer reviewe
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