دانلود مقاله ISI انگلیسی شماره 39951
عنوان فارسی مقاله

یک روش مشترک برای مدیریت دانش ضمنی: برنامه برای تحقیقات علمی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
39951 2016 6 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A collaborative methodology for tacit knowledge management: Application to scientific research
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Future Generation Computer Systems, Volume 54, January 2016, Pages 450–455

کلمات کلیدی
به اشتراک گذاری دانش - همکاری - وب معنایی - توسعه هستی شناسی - مدیریت دانش
پیش نمایش مقاله
پیش نمایش مقاله یک روش مشترک برای مدیریت دانش ضمنی: برنامه برای تحقیقات علمی

چکیده انگلیسی

Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.

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