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The seemingly simple task of reusing data for science education relies on the presence of scientific data, scientists willing to share, infrastructure to provide access, and mechanisms to share between the two disparate communities of scientists and science students. What makes sharing between scientists and science students a special case of data sharing, is that all of the implicit knowledge attending the data must pass along this same vector. Our work at the Center for Embedded Networked Sensing studying aspects of this data reuse problem has shown us a rough outline of how the future of this data sharing will look. Our approach is to start from the prospective of the scientists, looking for opportunities to support scientific research, and then leveraging the data for reuse by education. The investment needed to capture high quality scientific data necessitates the consideration of reuse by the general population as well as other interested scientific parties. IntroductionFor a digital library to be useful it must fit the needs, activities, and contexts of the people who use it, who create it, and who contribute to it. Here we report on the initial stages of research to develop and deploy a digital library of primary sources in habitat biology for use by scientists, teachers, and high school students associated with the Center for Embedded Networked Sensing (CENS), a large, multi-disciplinary research center. We are studying the information-related practices of these communities as input to the design.A basic premise of Science and Technology Studies (STS) is that science is a technical practice and a social practice (Star, 1995). In the case of CENS, multiple communities are using the same data collection instruments and resulting data. It is the interaction between technological and social aspects of scientific research that makes designing a system for these communities a complicated problem. When, how, and whether data sharing occurs between scientists is influenced by several conditions, such as whether scientific data exist to be shared, whether those scientists are willing to share those data, and whether mechanisms are available to support sharing. Sharing data among scientists reflects community practices, and these practices are only minimally understood (Hilgartner & Brandt-Rauf, 1994). Even less is understood about the conditions under which scientists will share their data with teachers and their students.Making scientific data available for use in learning is a means to leverage investments in the technology, the data, and the associated infrastructure. The CENS community initially consists of researchers across multiple disciplines, teachers, and students affiliated with the Center. As we expand, data generated by our sensor networks will be available to other scientists and to teachers and students in other schools. Sharing data among this diverse array of communities is the long-term goal of the research reported here. CENS offers a rare opportunity to study the generation of scientific data...
The seemingly simple task of reusing data for science education relies on the presence of scientific data, scientists willing to share, infrastructure to provide access, and mechanisms to share between the two disparate communities of scientists and science students. What makes sharing between scientists and science students a special case of data sharing, is that all of the implicit knowledge attending the data must pass along this same vector. Our work at the Center for Embedded Networked Sensing studying aspects of this data reuse problem has shown us a rough outline of how the future of this data sharing will look. Our approach is to start from the prospective of the scientists, looking for opportunities to support scientific research, and then leveraging the data for reuse by education. The investment needed to capture high quality scientific data necessitates the consideration of reuse by the general population as well as other interested scientific parties. IntroductionFor a digital library to be useful it must fit the needs, activities, and contexts of the people who use it, who create it, and who contribute to it. Here we report on the initial stages of research to develop and deploy a digital library of primary sources in habitat biology for use by scientists, teachers, and high school students associated with the Center for Embedded Networked Sensing (CENS), a large, multi-disciplinary research center. We are studying the information-related practices of these communities as input to the design.A basic premise of Science and Technology Studies (STS) is that science is a technical practice and a social practice (Star, 1995). In the case of CENS, multiple communities are using the same data collection instruments and resulting data. It is the interaction between technological and social aspects of scientific research that makes designing a system for these communities a complicated problem. When, how, and whether data sharing occurs between scientists is influenced by several conditions, such as whether scientific data exist to be shared, whether those scientists are willing to share those data, and whether mechanisms are available to support sharing. Sharing data among scientists reflects community practices, and these practices are only minimally understood (Hilgartner & Brandt-Rauf, 1994). Even less is understood about the conditions under which scientists will share their data with teachers and their students.Making scientific data available for use in learning is a means to leverage investments in the technology, the data, and the associated infrastructure. The CENS community initially consists of researchers across multiple disciplines, teachers, and students affiliated with the Center. As we expand, data generated by our sensor networks will be available to other scientists and to teachers and students in other schools. Sharing data among this diverse array of communities is the long-term goal of the research reported here. CENS offers a rare opportunity to study the generation of scientific data...
e-Research is intended to facilitate collaboration through distributed access to content, tools, and services. Lessons about collaboration are extracted from the findings of two large, long-term digital library research projects. Both the Alexandria Digital Earth Prototype Project (ADEPT) and the Center for Embedded Networked Sensing (CENS) project on data management leverage scientific research data for use in teaching. Two forms of collaboration were studied: (1) direct, in which faculty work together on research projects; and (2) indirect or serial, in which faculty use or contribute content to a common pool, such as teaching resources, concepts and relationships, or research data. Five aspects of collaboration in e-Research are discussed: (1) disciplinary factors, (2) incentives to adopt e-Learning and eResearch technologies, (3) user roles, (4) information sharing, and (5) technical requirements. Collaboration varied by research domain in both projects, and appears partly to be a function of the degree of instrumentation in data collection. Faculty members were more interested in tools to manage their own research data than in tools to facilitate teaching. They also were more reflective about their research than teaching activities. The availability of more content, tools, and services to incorporate primary data in teaching was only a minimal incentive to use these resources. Large investments in a knowledge base of scientific concepts and relationships for teaching did not result in re-use by other faculty during the course of the project. Metadata requirements for research and for teaching vary greatly, which further complicates the transfer of resources across applications. Personal digital libraries offer a middle ground between private control and public release of content, which is a promising direction for the design of digital libraries that will facilitate collaboration in e-Research.
The purpose of this study was to understand the organizational level decision factors in technology adoption in the context of digital libraries. A qualitative case study approach was used to investigate the adoption of a specific technology, XML-based Web services, in digital libraries. Rogers's diffusion of innovations and Wenger's communities of practice were the theories used to frame the study. The data collected through interviews were triangulated with documentary evidence and a comprehensive member check. Four organizational level influences identified when making technology adoption decisions in the context of digital libraries were organizational structure, management style, focus and direction of the program, and relationships with external entities. Attributes including program size, organizational culture and availability of financial resources contributed to these organizational level influences whereas program size did not appear to have an effect. Informal communication mechanisms were found to inform and influence the decision-making process.he speed of technological advances in information and communication technologies within the last two decades has enabled libraries to offer digital library services to create, develop, and provide innovative information resources and services. Digital libraries (DLs) bring enhanced and expanded services to libraries, add value to existing user services, and transform the information landscape by improving and changing the means of knowledge access, creation, use, and discovery across disciplines regardless of temporal and geographical barriers.1 Lesk defines a DL as a collection of organized information in digital format. 2The evolving information landscape presents challenges such as the lack of standards and ineffective information retrieval mechanisms.3 Interoperability is one such challenge that needs to be addressed by DLs because it is key to connecting disparate systems and resources. 4 The size, heterogeneity, and complexity of today's information resources and metadata standards are important variables to consider when building or integrating DLs because they pose immense challenges for interoperability.5 XMLbased web services (WS), a next generation of web-based technology for machine-todoi:10.5860/crl.77.3.314 crl15-695
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