NEON non-specialist use case; science data reuse in a classroom

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Presented at the AGU Fall Meeting 2012

Abstract:

We present our experience in bringing science data into the undergraduate classroom. In particular we have worked with scientists associated with the NSF-funded NEON (neoninc.org) project. We have developed a non-specialist use case aimed at undergraduate education. This exercise was developed to give the teacher/professor/facilitator the means to create a lesson plan that will allow students the opportunity to work with large, spatially diverse data sets on water quality and other ecological parameters of streams in the United States. The stream parameters investigated here are total nitrogen, total phosphorus and a macro invertebrate index for the 10 EPA regions in the contiguous US. Instructors would use this lesson as an opportunity to discuss the concept of “ecosystem health,” a controversial topic in science but with intuitive resonance among the general public.

However, current research data is highly specialized, lacking understandable, or all together lacking, metadata. This metadata is highly specialized, understandable by only the science specialist, or domain expert. Also, the data and metadata is difficult to locate by a non-specialist. The scientist knows where to find the data, how to collect the data, and can understand the structure of the data and what the data means. The meaning, the knowledge, the understanding is in the minds of the scientist. Thus, specific accommodation of the semantics for non-specialists is required.

We include a current description of the activity and its outcomes and discuss the effectiveness of our semantic web development methodology in developing this non-specialist use case.

History

DateCreated ByLink
December 4, 2012
03:45:03
Patrick WestDownload
December 2, 2012
19:51:10
Patrick WestDownload
December 1, 2012
11:33:13
Patrick WestDownload
November 30, 2012
17:37:15
Patrick WestDownload
November 13, 2012
02:04:14
Patrick WestDownload

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TW LogoNeon Educational System for Data Access and Analysis (NESDAA)
Principal Investigator: Peter Fox
Description: To enable advanced undergraduate students and facilitator to have access to learning materials and associated artefacts like data, code, workflows [e.g. Taverna], scientific literature, and more.

Related Research Areas:

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Description: None.
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At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

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