Ann Zimmerman

From Shared Databases to Communities of Practice: A Taxonomy of Collaboratories

Promoting affiliation between scientists is relatively easy, but creating larger organizational structures is much more difficult, due to traditions of scientific independence, difficulties of sharing implicit knowledge, and formal organizational barriers. The Science of Collaboratories (SOC) project conducted a broad five-year review to take stock of the diverse ecosystem of projects that fit our definition of a collaboratory and to distill lessons learned in the process. This article describes one of the main products of that review, a seven-category taxonomy of collaboratory types. The types are: Distributed Research Centers, Shared Instruments, Community Data Systems, Open Community Contribution Systems, Virtual Communities of Practice, Virtual Learning Communities, and Community Infrastructure Projects. Each of the types is defined and illustrated with one example, and key technical and organizational issues are identified.

Not by metadata alone: the use of diverse forms of knowledge to locate data for reuse

An important set of challenges for eScience initiatives and digital libraries concern the need to provide scientists with the ability to access data from multiple sources. This paper argues that an analysis of scientists‘ reuse of data prior to the advent of eScience can illuminate the requirements and design of digital libraries and cyberinfrastructure. As part of a larger study on data sharing and reuse, I investigated the processes by which ecologists locate data that were initially collected by others. Ecological data are unusually complex and present daunting problems of interpretation and analysis that must be considered in the design of cyberinfrastructure. The ecologists that I interviewed found ways to overcome many of these difficulties. One part of my results shows that ecologists use formal and informal knowledge that they have gained through disciplinary training and through their own data-gathering experiences to help them overcome hurdles related to finding, acquiring, and validating data collected by others. A second part of my findings reveals that ecologists rely on formal notions of scientific practice that emphasize objectivity to justify the methods they use to collect data for reuse. I discuss the implications of these findings for digital libraries and eScience initiatives.

Growing an infrastructure: the role of gateway organizations in cultivating new communities of users

Issues of scaling are critical when an infrastructure is trying to grow. Systems that worked well with smaller numbers or particular types of users must change to meet the needs of an expanding and diversified user base. A first step toward growth is to cultivate new users. We present results from research that examines one approach to the challenge of attracting new users to a large-scale computing infrastructure. We describe gateway organizations and the important social and technical support they provide, which help potential users to conceptualize a use for the infrastructure and increase their willingness and ability to use it.

Performance metrics and auditing framework using application kernels for high-performance computer systems

This paper describes XSEDE Metrics on Demand, a comprehensive auditing framework for use by high‐performance computing centers, which provides metrics regarding resource utilization, resource performance, and impact on scholarship and research. This role‐based framework is designed to meet the following objectives: (1) provide the user community with a tool to manage their allocations and optimize their resource utilization; (2) provide operational staff with the ability to monitor and tune resource performance; (3) provide management with a tool to monitor utilization, user base, and performance of resources; and (4) provide metrics to help measure scientific impact. Although initially focused on the XSEDE program, XSEDE Metrics on Demand can be adapted to any high‐performance computing environment. The framework includes a computationally lightweight application kernel auditing system that utilizes performance kernels to measure overall system performance. This allows continuous resource auditing to measure all aspects of system performance including filesystem performance, processor and memory performance, and network latency and bandwidth. Metrics that focus on scientific impact, such as publications, citations and external funding, will be included to help quantify the important role high‐performance computing centers play in advancing research and scholarship. Copyright

Special Theme: Project Management in E-Science: Challenges and Opportunities

In this introduction to the special theme: Project Management in e-Science: Challenges and Opportunities, we argue that the role of project management and different forms of leadership and facilitation can influence significantly the nature of cooperation and its outcomes and deserves further research attention. The quality of social interactions such as communication, cooperation, and coordination, have emerged as key factors in developing and deploying e-science infrastructures and applications supporting large-scale and distributed collaborative scientific research. If software is seen to embody the relational web within which it evolves, and if the processes of software design, development and deployment are seen as ongoing transformations of this dynamic web of relationships between technology, people and environment, the role of managers becomes crucial: it is their responsibility to balance and facilitate the dynamics of these relationships.

Performance metrics and auditing framework for high performance computer systems

This paper describes a comprehensive auditing framework, XDMoD, for use by high performance computing centers to readily provide metrics regarding resource utilization (CPU hours, job size, wait time, etc), resource performance, and the centers impact in terms of scholarship and research. This role-based auditing framework is designed to meet the following objectives: (1) provide the user community with an easy to use tool to oversee their allocations and optimize their use of resources, (2) provide staff with easy access to performance metrics and diagnostics to monitor and tune resource performance for the benefit of the users, (3) provide senior management with a tool to easily monitor utilization, user base, and performance of resources, and (4) help ensure that the resources are effectively enabling research and scholarship. XDMoD is initially focused on the NSF TeraGrid (TG) and follow-on XSEDE (XD) program, where it will become a key component of the TG/XSEDE User Portal. However, this auditing system is intended to have a general applicability to any HPC system or center. The XDMoD auditing system is architected using a set of modular components that facilitate the utilization of community contributed components information. It includes an active and reactive (as opposed to passive) service set accessible through a variety of endpoints such as web-based user interface, RESTful web services, and provided development tools. One component also provides a computationally lightweight and flexible application kernel auditing system that reflects best-in-class performance kernels to measure overall system performance with respect to existing applications that are actually being run by users. This allows continuous resource auditing to monitor all aspects of system performance, most critically from a completely user-centric point of view.