Seeking activity: on the trail of users in open and community source frameworks

Usage data captured and logged by computers has long been an essential source of information for software developers, support services personnel, usability designers, and learning researchers [1, 2]. Whether from mainframes, file servers, network devices, or workstations, the user event data logged in its many forms has served as an essential source of information for those who need to improve software, analyze problems, monitor security, track workflow, report on resource usage, evaluate learning activities etc. With today's generation of open and community source web-based frameworks, however, new challenges arise as to how, where, and when user activity gets captured and analyzed. These frameworks' flexibility in allowing easy integration of different applications, presentation technologies, middleware, and data sources has side effects on usage data: fragmented logs in a wide range of formats often bestrewn across many locations. This paper focuses on common issues faced especially by academic computing support personnel who need to gather and analyze user activity information within heterogeneous, distributed open source web frameworks like Sakai and uPortal. As described in this paper, these kinds of challenges can be met by drawing upon techniques for coordinated distributed event monitoring along with some basic data mining and data visualization approaches. In particular, this paper describes a work-in-progress to develop an approach towards building a distributed capture and analysis systems for a large production deployment of the Sakai Collaboration and Learning Environment in order to meet a wide range of tracking, monitoring, and reporting log analysis in one university setting.

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