Harvesting for disseminating, open archives and role of academic libraries

The Scholarly communication system is in a critical stage, due to a number of factors.The Open Access movement is perhaps the most interesting response that the scientific community has tried to give to this problem. The paper examines strengths and weaknesses of the Open Access strategy in general and, more specifically, of the Open Archives Initiative, discussing experiences, criticisms and barriers. All authors that have faced the problems of implementing an OAI compliant e-print server agree that technical and practical problems are not the most difficult to overcome and that the real problem is the change in cultural attitude required. In this scenario the university library is possibly the standard bearer for the advent and implementation of e-prints archives and Open Archives services. To ensure the successful implementation of this service the Library has a number of distinct roles to play

BioWorkbench: A High-Performance Framework for Managing and Analyzing Bioinformatics Experiments

Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require high-performance computing (HPC) techniques and can benefit from specialized technologies such as Scientific Workflow Management Systems (SWfMS) and databases. In this work, we present BioWorkbench, a framework for managing and analyzing bioinformatics experiments. This framework automatically collects provenance data, including both performance data from workflow execution and data from the scientific domain of the workflow application. Provenance data can be analyzed through a web application that abstracts a set of queries to the provenance database, simplifying access to provenance information. We evaluate BioWorkbench using three case studies: SwiftPhylo, a phylogenetic tree assembly workflow; SwiftGECKO, a comparative genomics workflow; and RASflow, a RASopathy analysis workflow. We analyze each workflow from both computational and scientific domain perspectives, by using queries to a provenance and annotation database. Some of these queries are available as a pre-built feature of the BioWorkbench web application. Through the provenance data, we show that the framework is scalable and achieves high-performance, reducing up to 98% of the case studies execution time. We also show how the application of machine learning techniques can enrich the analysis process