فایل ورد کامل روش شناسی مشارکتی برای مدیریت دانش ضمنی: کاربرد آن در تحقیقات علمی

توجه : به همراه فایل word این محصول فایل پاورپوینت (PowerPoint) و اسلاید های آن به صورت هدیه ارائه خواهد شد

این مقاله، ترجمه شده یک مقاله مرجع و معتبر انگلیسی می باشد که به صورت بسیار عالی توسط متخصصین این رشته ترجمه شده است و به صورت فایل ورد (microsoft word) ارائه می گردد

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فایل ورد این مقاله بسیار خوب تایپ شده و قابل کپی و ویرایش می باشد و تنظیمات آن نیز به صورت عالی انجام شده است؛ به همراه فایل ورد این مقاله یک فایل پاور پوینت نیز به شما ارئه خواهد شد که دارای یک قالب بسیار زیبا و تنظیمات نمایشی متعدد می باشد

توجه : در صورت مشاهده بهم ریختگی احتمالی در متون زیر ،دلیل ان کپی کردن این مطالب از داخل فایل می باشد و در فایل اصلی فایل ورد کامل روش شناسی مشارکتی برای مدیریت دانش ضمنی: کاربرد آن در تحقیقات علمی،به هیچ وجه بهم ریختگی وجود ندارد

تعداد صفحات این فایل: ۲۰ صفحه

در این مقاله، ما یک روش شناسی دو مرحله ای کلی ارائه کردیم که به مفهوم سازی و رسمیت دادن مشارکتی به دانش ضمنی متخصصان در درون یک تیم اختصاص دارد. این روش شناسی موانع انسان را مد نظر قرار می دهد و یک رویکرد چند مرحله ای را به منظور ایجاد یک آنتولوژی مرکزی با توصیف مفاهیم کلی، و آنتولوژی خاص آن حوزه که نشان دهنده مهارت های متخصصان می باشد اتخاذ می کند. ما نتایج به کار گیری این روش شناسی در خصوص مدیریت فعالیت های تحقیقاتی علمی را ارائه کردیم و یک پایگاه وب معنایی ایجاد کردیم تا دانش ضمنی متخصصان تیم مان را مدیریت کنیم. روش شناسی پیشنهاد شده بر اساس بازخوردهای کاربران و کیفیت تجربیات شان مورد ارزیابی قرار گرفت.
در حال حاضر ما عمدتا بر روی اتوماتیک کردن فرایند کسب دانش از طریق درک یک سرویس بازیابی اطلاعات هوشمند کار می کنیم که به تکامل لحظه ای آنتولوژی کمک می کند کار می کنیم. کار آتی ما بر نگهداری و استدلال دانش متمرکز خواهد بود.

عنوان انگلیسی:A collaborative methodology for tacit knowledge management: Application to scientific research~~en~~

Introduction Research collaboration plays an important role in evaluating the research team outcomes [1,2]. Successful collaborations take place if research team members and/or external partners can smoothly communicate based on a sharable knowledge that reflects the team skills [3]. Currently, scientific research team knowledge is embedded in unstructured documents including published articles, internal team reports, figures, tables and videos representing demonstrations. Thus, information is everywhere, heterogeneous and poorly organized which hamper knowledge exchange and sharing, and make information seeking is time-consuming. Advances in Knowledge Management (KM) based on Information Technology (IT) provide important means to increase productivity and achieve the team effectiveness [4] since it provides methods and tools that capture, understand, share, and facilitate knowledge access and reuse by team members to create value [5–۷]. However, IT support cannot cover more than 10%–۳۰% of KM [8]. More importantly, domain experts are the main knowledge source. Face-to-face interactions such as interviews, brainstorming, meetings, etc. are the keys for elucidating, capturing and sharing experts’ tacit knowledge [9]. It is worth mentioning that the success of KM, especially which relies on the knowledge of experts, strongly depends on the acceptance of people involved in this process. At this end, human collaboration and participation is required to underpin an efficient knowledge transfer and sharing. Nevertheless, some cultural and social factors may hinder the progress of this process, especially if members may feel and think that knowledge sharing depletes the time and the efforts that can be invested in other activities more beneficial for themselves [10]. Moreover, each member has his/her own personality traits and characteristics, which makes managing a group of person complex, in particular if conflicts appear. Consequently, to handle human barriers that may hamper extracting and sharing the experts’ tacit knowledge, we propose a generic two-step methodology that describes processes and actors involved in the conceptualization and knowledge creation based on a multi-level approach. The objective of proposing a multi-level approach is to identify as a first stage a generic domain level that can be reused by any community/group of users interested to this domain, then extending it to support the user-requirements. We applied the proposed methodology to formalize and classify the scientific research activities within our SARA research team.1 The rest of the paper is organized as follow. Section 2 draws our proposed generic two-step methodology for experts’ tacit knowledge conceptualization. Section 3 provides the results of applying the proposed methodology to formalize the tacit knowledge of our team experts. Section 4 presents our preliminary evaluation of the efficiency of the proposed methodology. Section 5 details existing researches dealing with collaborative scientific knowledge management and describes existing methodologies for building ontologies. Finally, Section 6 summaries our contribution and identifies our future research works. ۲ A generic two-step methodology for building ontology Our methodology follows a top-down approach [11] which is mainly composed on two steps as shown in Fig. 1: the ‘‘Knowledge Organization’’ that corresponds to conceptualizing and representing the knowledge in an appropriate format; and the ‘‘Knowledge Acquisition and Reuse’’ that allows the users collaboratively producing and consuming the knowledge. The ‘‘Knowledge Organization’’ represents the fundamental step. First, it identifies a core ontological model named Core Reference Ontology (CRO) describing the generic concepts and relations according to the formalized requirements. Then, it specializes these concepts to reflect the domain experts’ skills and knowledge based on their collaboration, and generates the Domain Specific Ontology (DSO). The main contribution of this methodology is to avoid conflicts and human barriers related to the personality characteristics when communicating with experts. Based on an incremental approach, requirements are captured and refined with the collaboration of the leader expert. Thus, the key concepts of CRO, inference and inconsistency rules are identified (1, 2). After preparing the list of concepts and relations, the knowledge engineer identifies existing upper ontologies that can be reused and easily integrated with the CRO (3). To personalize the CRO in a specific domain, the domain experts are involved to enrich the CRO with their own vision and tacit knowledge. It is truism that each person has his/her specific character and manners to communicate and express his/her knowledge. Studies in psychology have shown that knowledge sharing behavior among individuals is influenced by personality traits [12]. According to Pervin [13], personality refers ‘‘to an individual’s unique and stable pattern of thinking, feeling, acting and reacting to his or her social environment’’.

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