<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Juri Dachtera</style></author><author><style face="normal" font="default" size="100%">Pipek, Volkmar</style></author><author><style face="normal" font="default" size="100%">Wulf, Volker</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Sharing Knowledge and Expertise: The CSCW View of Knowledge Management</style></title><secondary-title><style face="normal" font="default" size="100%">Computer Supported Cooperative Work (CSCW) Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">collective intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">cscw</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">QA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">531-573</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Knowledge Management (KM) is a diffuse and controversial term, which has been used by a large number of research disciplines. CSCW, over the last 20 years, has taken a critical stance towards most of these approaches, and instead, CSCW shifted the focus towards a practice-based perspective. This paper surveys CSCW researchers’ viewpoints on what has become called ‘knowledge sharing’ and ‘expertise sharing’. These are based in an understanding of the social contexts of knowledge work and practices, as well as in an emphasis on communication among knowledgeable humans. The paper provides a summary and overview of the two strands of knowledge and expertise sharing in CSCW, which, from an analytical standpoint, roughly represent ’generations’ of research: an ’object-centric’ and a ’people-centric’ view. We also survey the challenges and opportunities ahead.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaomu Zhou</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Kai Zheng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CPOE workarounds, boundary objects, and assemblages</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI’11)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">assemblage</style></keyword><keyword><style  face="normal" font="default" size="100%">boundary object</style></keyword><keyword><style  face="normal" font="default" size="100%">CPOE</style></keyword><keyword><style  face="normal" font="default" size="100%">cscw</style></keyword><keyword><style  face="normal" font="default" size="100%">EHR</style></keyword><keyword><style  face="normal" font="default" size="100%">electronic patient records</style></keyword><keyword><style  face="normal" font="default" size="100%">health informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">health information</style></keyword><keyword><style  face="normal" font="default" size="100%">information access</style></keyword><keyword><style  face="normal" font="default" size="100%">medical informatics</style></keyword><keyword><style  face="normal" font="default" size="100%">medical information</style></keyword><keyword><style  face="normal" font="default" size="100%">medical orders</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">5/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We conducted an ethnographically based study at a large teaching hospital to examine clinician workarounds engendered by the adoption of a Computerized Prescribe Order Entry (CPOE) system. Specifically, we investigated how adoption of computerized systems may alter medical practice, order management in particular, as manifested through the working-around behavior developed by doctors and nurses to accommodate the changes in their day-to-day work environment. In this paper, we focus on clinicians’ workarounds, including those workarounds that gradually disappeared and those that have become routinized. Further, we extend the CSCW concept of boundary object (to &quot;assemblage&quot;) in order to understand the workarounds created with CPOE system use and the changing nature of clinical practices that are increasingly computerized.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhang, Jun</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Lada A. Adamic</style></author><author><style face="normal" font="default" size="100%">Kevin K. Nam</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">QuME: A Mechanism to Support Expertise Finding in Online Help-seeking Communities</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology (UIST&#039;07)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cscw</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise location</style></keyword><keyword><style  face="normal" font="default" size="100%">social networks</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">111–114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Help-seeking communities have been playing an increasingly critical role in the way people seek and share information. However, traditional help-seeking mechanisms of these online communities have some limitations. In this paper, we describe an expertise-finding mechanism that attempts to alleviate the limitations caused by not knowing users&#039; expertise levels. As a result of using social network data from the online community, this mechanism can automatically infer expertise level. This allows, for example, a question list to be personalized to the user&#039;s expertise level as well as to keyword similarity. We believe this expertise location mechanism will facilitate the development of next generation help-seeking communities.&lt;/p&gt;
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