Leveraging HTC for UK eScience with very large Condor pools: demand for transforming untapped power into results

We provide an insight into the demand from the UK eScience community for very large HighThroughput Computing resources and provide an example of such a resource in current productionuse: the 930-node eMinerals Condor pool at UCL. We demonstrate the significant benefits thisresource has provided to UK eScientists via quickly and easily realising results throughout a rangeof problem areas. We demonstrate the value added by the pool to UCL I.S infrastructure andprovide a case for the expansion of very large Condor resources within the UK eScience Gridinfrastructure. We provide examples of the technical and administrative difficulties faced whenscaling up to institutional Condor pools, and propose the introduction of a UK Condor/HTCworking group to co-ordinate the mid to long term UK eScience Condor development, deploymentand support requirements, starting with the inaugural UK Condor Week in October 2004

An Evaluation of eScience Lab Kits for Online Learning

Higher education online science courses generally lack the hands-on components essential in understanding theories, methods, and techniques in chemistry and biology. Companies like eScience Labs construct kits to facilitate online learning, which provide students with hands-on activities relevant to their science courses. In order to evaluate ease, efficacy, and comprehension of the forensic science kits by eScience Labs was completed while writing observations of the activities during and after completion; the lab manual learning objectives were compared to results of activities and two stopwatches took elapsed time of each activity to compare with the stated times in the kit manual. This method determined that the eScience manual does not provide enough information for a college freshman to fully understand the topic; however, combining these labs with professor provided online lectures would allow full comprehension of the forensic science applications or techniques. Recommendations to obtain maximum learning outcomes include requiring the completion of prerequisites like algebra and general chemistry. With these aspects combined, the eScience lab kit is a great addition to an introductory forensic science course as it provides safe and interactive hands-on activities

eScience Thesaurus 2.0

Objective: The eScience Thesaurus (http://esciencelibrary.umassmed.edu/professional-educ/escience-thesaurus) is an online resource which connects and defines concepts, services, and tools relevant to librarians supporting eScience research. A Thesaurus’ term’s record also showcases relevant literature, resources, and video interviews with librarians working in the field of eScience. The original eScience Thesaurus was created by Kevin Read in 2013 and there have been many developments in eScience which prompted a revision of this valuable resource. To update the eScience Thesaurus, one of the current Library Fellows at the Lamar Soutter Library revised the methodology employed by Read, Creamer, Kafel, Vander Hart, & Martin (2013) to review the eScience literature and develop a list of new terms for the Thesaurus. Methods: To identify new terms, the Fellow replicated the search strategy used by Read et al. (2013) and limited the search to articles since 2013 and subsequently tagged relevant articles with their prominent topics. The prominent topics outside of the current terms in the thesaurus were suggested as possible new thesaurus topics. On top of identifying new terms, the Library Fellow suggested current terms that could be merged with other terms in the thesaurus. Both the current thesaurus terms and new proposed thesaurus terms were evaluated by the eScience Portal Editorial Board for inter-coder reliability. Results: Of the 55 terms currently in the eScience Thesaurus, 10 were identified for merging. After reviewing the eScience literature, the Library Fellow suggested 47 terms for the Editorial Board to review and members of the Editorial Board added 12 terms to the list which were reviewed by the whole group as well. Of the 59 total terms suggested, 23 were chosen as new terms to be added to the eScience Thesaurus. Conclusion: The next steps in the eScience Thesaurus’ revitalization are creating records for the new terms, including literature citations, resources, and interviews with subject experts; and sending out groups of the revised and new term records to the Editorial Board and additional eScience subject experts for review. Look for the new and updated eScience Thesaurus coming soon! Read, K., Creamer, A., Kafel, D., Vander Hart, R.J., & Martin, E.R. (2013). Building an escience thesaurus for librarians: A collaboration between the National Network of Libraries of Medicine, New England Region and an Associate Fellow at the National Library of Medicine. Journal of eScience Librarianship, 2(2), 53-67. http://dx.doi.org/10.7191/jeslib.2013.104

Building an eScience Thesaurus for Librarians: A Collaboration Between the National Network of Libraries of Medicine, New England Region and an Associate Fellow at the National Library of Medicine

Objective: In response to the growing interest and adoption of eScience roles by librarians, those from the National Network of Libraries of Medicine, New England Region (NN/LM NER) and an Associate Fellow from the National Library of Medicine collaborated to build an eScience Thesaurus. The Thesaurus will introduce librarians to terminology and concepts in eScience, point to relevant literature and resources on data and digital research topics, and provide links to interviews with librarians and experts working in eScience-related roles. The eScience Thesaurus is a starting place for librarians to find the vocabulary to research the background, resources, and tools necessary for developing their capacity to provide eScience-related services. Methods: The Associate Fellow completed a review of eScience-related literature to identify the seminal publications for the originations of these terms and concepts as they apply to libraries. Next, the Associate Fellow worked with the NN/LM NER to compile an environmental scan of resources that would be useful and applicable for librarians, and created a scope document and record structure. The team interviewed prominent librarians working in eScience roles and experts that have created digital tools and services used by the library community. Finally, the team sent the Thesaurus records out to five members of the advisory and editorial review boards from the eScience Portal for New England Librarians for evaluation. Results: The eScience Thesaurus is now hosted on the eScience Portal for New England Librarians’ website. It provides a comprehensive list of more than 50 different terminologies and concepts, with links to seminal and relevant literature, resources, grants, and interviews on a variety of eScience-related topics. Conclusion: The eScience Thesaurus is an evolving resource; as the field expands and more eScience-related terms are adopted by the library and information science community, the Portal will enable its users to electronically submit new vocabulary and records to the Thesuarus, thus preserving it as a go-to eScience resource for librarians

An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Integrated Findings to Develop Research Data Services

This article reports on the integrated findings of an exploratory sequential mixed methods research design aimed to understand data management behaviors and challenges of faculty at the University of Vermont (UVM) in order to develop relevant research data services. The exploratory sequential mixed methods design is characterized by an initial qualitative phase of data collection and analysis, followed by a phase of quantitative data collection and analysis, with a final phase of integration or linking of data from the two separate strands of data. A joint display was used to integrate data focused on the three primary research questions: How do faculty at UVM manage their research data, in particular how do they share and preserve data in the long-term?; What challenges or barriers do UVM faculty face in effectively managing their research data?; and What institutional data management support or services are UVM faculty interested in? As a result of the analysis, this study suggests four major areas of research data services for UVM to address: infrastructure, metadata, data analysis and statistical support, and informational research data services. The implementation of these potential areas of research data services is underscored by the need for cross-campus collaboration and support

An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Findings from the Qualitative Phase

The objective of this article is to report on the first qualitative phase of an exploratory sequential mixed methods research design focused on researcher data management practices and related institutional research data services. The aim of this study is to understand data management behaviors of faculty at the University of Vermont (UVM), a higher-research activity Research University, in order to guide the development of campus research data management services. The population of study was all faculty who received National Science Foundation (NSF) grants between 2011 and 2014 who were required to submit a data management plan (DMP); qualitative data was collected in two forms: (1) semi-structured interviews and (2) document analysis of data management plans. From a population of 47 researchers, six were included in the interview sample, representing a broad range of disciplines and NSF Directorates, and 35 data management plans were analyzed. Three major themes were identified through triangulation of qualitative data sources: data management activities, including data dissemination and data sharing; institutional research support and infrastructure barriers; and perceptions of data management plans and attitudes towards data management planning. The themes articulated in this article will be used to design a survey for the second quantitative phase of the study, which will aim to more broadly generalize data management activities at UVM across all disciplines

An Exploratory Sequential Mixed Methods Approach to Understanding Researchers’ Data Management Practices at UVM: Findings from the Quantitative Phase

This article reports on the second quantitative phase of an exploratory sequential mixed methods research design focused on researcher data management practices and related institutional support and services. The study aims to understand data management activities and challenges of faculty at the University of Vermont (UVM), a higher research activity Research University, in order to develop appropriate research data services (RDS). Data was collected via a survey, built on themes from the initial qualitative data analysis from the first phase of this study. The survey was distributed to a nonrandom census sample of full-time UVM faculty and researchers (P=1,190); from this population, a total of 319 participants completed the survey for a 26.8% response rate. The survey collected information on five dimensions of data management: data management activities; data management plans; data management challenges; data management support; and attitudes and behaviors towards data management planning. Frequencies, cross tabulations, and chi-square tests of independence were calculated using demographic variables including gender, rank, college, and discipline. Results from the analysis provide a snapshot of research data management activities at UVM, including types of data collected, use of metadata, short- and long-term storage of data, and data sharing practices. The survey identified key challenges to data management, including data description (metadata) and sharing data with others; this latter challenge is particular impacted by confidentiality issues and lack of time, personnel, and infrastructure to make data available. Faculty also provided insight to RDS that they think UVM should support, as well as RDS they were personally interested in. Data from this study will be integrated with data from the first qualitative phase of the research project and analyzed for meta-inferences to help determine future research data services at UVM

Understanding eScience: Reflections on a Houston Symposium

EScience is a research methodology combining data collection, storage and networking on a massive scale. By its very nature, eScience presents new and diverse opportunities in librarianship. While various academic institutions such as Cornell, Georgia Tech, and the University of Massachusetts are already engaged in well-established projects at their libraries, eScience is still relatively new to many others. To explain eScience and its implications for medical librarians within the Texas Medical Center, The Texas Medical Center (TMC) Library hosted an event on February 13, 2012, called Understanding eScience: A Symposium for Medical Librarians. Funded in part by the National Network of Libraries of Medicine--South Central Region (NN/LM-SCR), this symposium’s core was a panel of scientists and librarians serving various roles in eScience research. These experts described their work to identify concrete opportunities and challenges for libraries hoping to take on similar roles. Designed with an emphasis on medical librarians, the symposium provided an educational and collaborative opportunity for librarians of all specialties. Within this article, the authors share their experiences in planning and hosting an eScience event and the catalyst it provided for The TMC Library’s on-going involvement in eScience research and collaborations

A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud Infrastructures

Resource allocation is today an integral part of cloud infrastructures management to efficiently exploit resources. Cloud infrastructures centers generally use custom built heuristics to define the resource allocations. It is an immediate requirement for the management tools of these centers to have a fast yet reasonably accurate simulation and evaluation platform to define the resource allocation for cloud applications. This work proposes a framework allowing users to easily specify mappings for cloud applications described in the AMALTHEA format used in the context of the DreamCloud European project and to assess the quality for these mappings. The two quality metrics provided by the framework are execution time and energy consumption.Comment: 2nd International Workshop on Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing DREAMCloud 2016 (arXiv:cs/1601.04675