915 resultados para Knowledge base maintenance
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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L'innovazione delle tecnologie di sequenziamento negli ultimi anni ha reso possibile la catalogazione delle varianti genetiche nei campioni umani, portando nuove scoperte e comprensioni nella ricerca medica, farmaceutica, dell'evoluzione e negli studi sulla popolazione. La quantità di sequenze prodotta è molto cospicua, e per giungere all'identificazione delle varianti sono necessari diversi stadi di elaborazione delle informazioni genetiche in cui, ad ogni passo, vengono generate ulteriori informazioni. Insieme a questa immensa accumulazione di dati, è nata la necessità da parte della comunità scientifica di organizzare i dati in repository, dapprima solo per condividere i risultati delle ricerche, poi per permettere studi statistici direttamente sui dati genetici. Gli studi su larga scala coinvolgono quantità di dati nell'ordine dei petabyte, il cui mantenimento continua a rappresentare una sfida per le infrastrutture. Per la varietà e la quantità di dati prodotti, i database giocano un ruolo di primaria importanza in questa sfida. Modelli e organizzazione dei dati in questo campo possono fare la differenza non soltanto per la scalabilità, ma anche e soprattutto per la predisposizione al data mining. Infatti, la memorizzazione di questi dati in file con formati quasi-standard, la dimensione di questi file, e i requisiti computazionali richiesti, rendono difficile la scrittura di software di analisi efficienti e scoraggiano studi su larga scala e su dati eterogenei. Prima di progettare il database si è perciò studiata l’evoluzione, negli ultimi vent’anni, dei formati quasi-standard per i flat file biologici, contenenti metadati eterogenei e sequenze nucleotidiche vere e proprie, con record privi di relazioni strutturali. Recentemente questa evoluzione è culminata nell’utilizzo dello standard XML, ma i flat file delimitati continuano a essere gli standard più supportati da tools e piattaforme online. È seguita poi un’analisi dell’organizzazione interna dei dati per i database biologici pubblici. Queste basi di dati contengono geni, varianti genetiche, strutture proteiche, ontologie fenotipiche, relazioni tra malattie e geni, relazioni tra farmaci e geni. Tra i database pubblici studiati rientrano OMIM, Entrez, KEGG, UniProt, GO. L'obiettivo principale nello studio e nella modellazione del database genetico è stato quello di strutturare i dati in modo da integrare insieme i dati eterogenei prodotti e rendere computazionalmente possibili i processi di data mining. La scelta di tecnologia Hadoop/MapReduce risulta in questo caso particolarmente incisiva, per la scalabilità garantita e per l’efficienza nelle analisi statistiche più complesse e parallele, come quelle riguardanti le varianti alleliche multi-locus.
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Software-maintenance offshore outsourcing (SMOO) projects have been plagued by tedious knowledge transfer during the service transition to the vendor. Vendor engineers risk being over-strained by the high amounts of novel information, resulting in extra costs that may erode the business case behind offshoring. Although stakeholders may desire to avoid these extra costs by implementing appropriate knowledge transfer practices, little is known on how effective knowledge transfer can be designed and managed in light of the high cognitive loads in SMOO transitions. The dissertation at hand addresses this research gap by presenting and integrating four studies. The studies draw on cognitive load theory, attributional theory, and control theory and they apply qualitative, quantitative, and simulation methods to qualitative data from eight in-depth longitudinal cases. The results suggest that the choice of appropriate learning tasks may be more central to knowledge transfer than the amount of information shared with vendor engineers. Moreover, because vendor staff may not be able to and not dare to effectively self-manage learn-ing tasks during early transition, client-driven controls may be initially required and subsequently faded out. Collectively, the results call for people-based rather than codification-based knowledge management strategies in at least moderately specific and complex software environments.
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The existing literature suggests that transitions in software-maintenance offshore outsourcing projects are prone to knowledge transfer blockades, i.e. situations in which the activities that would yield effective knowledge transfer do not occur, and that client management involvement is central to overcome them. However, the theoretical understanding of the knowledge transfer blockade is limited, and the reactive management behavior reported in case studies suggests that practitioners may frequently be astonished by the dynamics that may give rise to the blockade. Drawing on recent research from offshore sourcing and reference theories, this study proposes a system dynamics framework that may explain why knowledge transfer blockades emerge and how and why client management can overcome the blockade. The results suggest that blockades may emerge from a vicious circle of weak learning due to cognitive overload of vendor staff and resulting negative ability attributions that result in reduced helping behavior and thus aggravate cognitive load. Client management may avoid these vicious circles by selecting vendor staff with strong prior related experience. Longer phases of coexistence of vendor staff and subject matter experts and high formal and clan controls may also mitigate vicious circles.
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Knowledge processes are critical to outsourced software projects. According to outsourcing research, outsourced software projects succeed if they manage to integrate the client’s business knowledge and the vendor’s technical knowledge. In this paper, we submit that this view may not be wrong, but incomplete in a significant part of outsourced software work, which is software maintenance. Data from six software-maintenance outsourcing transitions indicate that more important than business or technical knowledge can be application knowledge, which vendor engineers acquire over time during practice. Application knowledge was the dominant knowledge during knowledge transfer activities and its acquisition enabled vendor staff to solve maintenance tasks. We discuss implications for widespread assumptions in outsourcing research.
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Knowledge acquisition and model maintenance are key problems in knowledge engineering to improve the productivity in the development of intelligent systems. Although historically a number of technical solutions have been proposed in this area, the recent experience shows that there is still an important gap between the way end-users describe their expertise and the way intelligent systems represent knowledge. In this paper we propose an original way to cope with this problem based on electronic documents. We propose the concept of intelligent document processor as a tool that allows the end-user to read/write a document explaining how an intelligent system operates in such a way that, if the user changes the content of the document, the intelligent system will react to these changes. The paper presents the structure of such a document based on knowledge categories derived from the modern knowledge modeling methodologies together with a number of requirements to be understandable by end-users and problem solvers.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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Transportation Systems Center, Cambridge, Mass.
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"October 1971."
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"10 October 1989."
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"9 October 1982."
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Includes index.