1,346 research outputs found

    ENHANCED BI SYSTEMS WITH ON-DEMAND DATA BASED ON SEMANTIC-ENABLED ENTERPRISE SOA

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    Since the 1990s, companies have been investing into IT infrastructure initiatives such as Enterprise Resource Planning (ERP) systems, Supply Chain Management (SCM) systems, and Customer Relationship Management (CRM) systems in order to increase efficiency, effectiveness, and internal process integration, among other goals. The current value of Business Intelligence (BI) for companies could be summarized by two main achievements: improvement of management of processes and improvement of operational processes. This paper will identify current requirements of BI and present a linkage to service-oriented architectures including added-values. Semantic-enabled Enterprise Service-Oriented Architecture (SESOA) is an enterprise solution that links businesses to external systems based on Web Services and SOA concept. It represents a lightweight web application that annotates Web Services that are coming from different service providers with semantics so that the indexing and discovery of these services can be more comprehensive. BI applications can be considered as service consumers in SESOA and can discover, select and invoke the services supplied by the external systems (service providers). In this way, SESOA forms the bridge between SOA and BI concepts to deliver in real time the ?on-demand? data as services and this opens the BI market to include SMEs as main resources of these services

    Investigating the use of semantic technologies in spatial mapping applications

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    Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend

    Grand Challenges of Traceability: The Next Ten Years

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    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

    Grand Challenges of Traceability: The Next Ten Years

    Full text link
    In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

    Experimental Evaluation of a Process Benchmarking Tool in a Green Business Process Management Context

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    Using a combination of metamodels, ontologies, green performance indicators and metrics, we apply a novel approach in Semantic Business Process Benchmarking to the area of Green Business Process Management (Green BPM). Up to now, process benchmarking has mainly been a manual process; the approach described and empirically evaluated in this paper partially automates the time-consuming and costly process analyses while introducing more flexibility regarding varying terminology, level of abstraction and modeling notation. Also, overviews of literature relevant to the field of Green Semantic BPM and commonly applied metrics in a Green BPM context are given

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

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    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

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    Within an enterprise, various stakeholders create different conceptual models, such as process, data, and requirements models. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they differ in focus, use different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artifacts; as such, they typically lack consistency and interoperability. This issue can be solved by enterprise-specific ontologies, which serve as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models interoperable and facilitates model integration. The challenge to accomplish this is twofold: on the one hand, an up-to-date enterprise-specific ontology needs to be created and maintained, and on the other hand, different modelers also need to be supported in their use of the enterprise-specific ontology. The authors propose to tackle these challenges by means of a recommendation-based conceptual modeling and an ontology evolution framework, and we focus in particular on ontology-based modeling support. To this end, the authors present a framework for Business Process Modeling Notation (BPMN) as a conceptual modeling language, and focus on how modelers can be assisted during the modeling process and how this impacts the semantic quality of the resulting models. Subsequently, a first, large-scale explorative experiment is presented involving 140 business students to evaluate the BPMN instantiation of our framework. The experiments show promising results with regard to incurred overheads, intention of use and model interoperability

    User Interaction with Linked Data: An Exploratory Search Approach

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    NoIt is becoming increasingly popular to expose government and citywide sensor data as linked data. Linked data appears to offer a great potential for exploratory search in supporting smart city goals of helping users to learn and make sense of complex and heterogeneous data. However, there are no systematic user studies to provide an insight of how browsing through linked data can support exploratory search. This paper presents a user study that draws on methodological and empirical underpinning from relevant exploratory search studies. The authors have developed a linked data browser that provides an interface for user browsing through several datasets linked via domain ontologies. In a systematic study that is qualitative and exploratory in nature, they have been able to get an insight on central issues related to exploratory search and browsing through linked data. The study identifies obstacles and challenges related to exploratory search using linked data and draws heuristics for future improvements. The authors also report main problems experienced by users while conducting exploratory search tasks, based on which requirements for algorithmic support to address the observed issues are elicited. The approach and lessons learnt can facilitate future work in browsing of linked data, and points at further issues that have to be addressed
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