Expertise-based peer selection in Peer-to-Peer networks

Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure, we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment, we show how expertise-based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages

Soft peer review: social software and distributed scientific evaluation

The debate on the prospects of peer-review in the Internet age and the increasing criticism leveled against the dominant role of impact factor indicators are calling for new measurable criteria to assess scientific quality. Usage-based metrics offer a new avenue to scientific quality assessment but face the same risks as first generation search engines that used unreliable metrics (such as raw traffic data) to estimate content quality. In this article I analyze the contribution that social bookmarking systems can provide to the problem of usage-based metrics for scientific evaluation. I suggest that collaboratively aggregated metadata may help fill the gap between traditional citation-based criteria and raw usage factors. I submit that bottom-up, distributed evaluation models such as those afforded by social bookmarking will challenge more traditional quality assessment models in terms of coverage, efficiency and scalability. Services aggregating user-related quality indicators for online scientific content will come to occupy a key function in the scholarly communication system

Recruitment and selection in Europe: one step beyond

No abstract available

Deeper Capacity Building for Greater Impact: Designing a Long-Term Initiative to Strengthen a Set of Nonprofit Organizations

Offers advice about how to plan, implement, and evaluate long-term, capacity-building initiatives -- sustained efforts to help a select group of nonprofit grantees reach a new level of effectiveness

Making Disciples: The Effects of Technology Integration Coaching

This paper describes a pilot study of collegial coaching for technology integration at two private Christian schools. Two students nearing completion of a Master’s in Education in Curriculum and Instruction with a Specialization in Instructional Technology each coached three fellow teachers, self-described as digital immigrants, to integrate technology into their teaching. The coaches spent an average of 15 hours per teacher brainstorming, teaching, and facilitating technology integration. Information obtained from a variety of data sources (interviews, a post-coaching questionnaire, a focus group, and analyses of journals kept by both coaches and coached teachers) revealed the positive effects of their collegial coaching and suggested ideas for optimizing coaching for technology integration