Stephan Zednik

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A challenge in providing scientific data services to a broad user base is to also provide the metadata services and tools the user base needs to correctly interpret and trust the provided data. Provenance metadata is especially vital to establishing trust, giving the user information on the conditions under which the data originated and any processing that(More)
Ontologies are increasingly deployed as a computer-accessible representation of key semantics in various parts of a data life cycle and, thus, ontology dynamics may pose challenges to data management and re-use. By using examples in the field of geosciences, we analyze challenges raised by ontology dynamics, such as heavy reworking of data, semantic(More)
The important topic of global climate change builds on a huge collection of scientific research. It is common for agencies releasing climate change information to be served with requests for all supporting materials resulting in a particular conclusion. Capturing and presenting global change provenance, linking to the research papers, data sets, models,(More)
Web-based science analysis and processing tools allow users to access, analyze, and generate visualizations for vast amounts of data without requiring the user to directly manage the data or the data analysis processes or understand the limits on the underlying data. These tools have the potential to provide a significant productivity increase to science(More)
The National Climate Assessment of the U.S. Global Change Research Program (USGCRP) analyzes and presents the impacts of climate change on the United States. The provenance information in the assessment is important because the assessment findings are of great public and academic concern and are used in policy and decision-making. By applying a use(More)
In this paper, we describe how a semantic webbased provenance Interlingua called the Proof Markup Language (PML) has been used to encode workflow provenance in a variety of diverse application areas. We highlight some usability and interoperability challenges that arose in the application areas and show how PML was used in the solutions.
Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the(More)
Data interoperability is an ongoing challenge for global open data initiatives. The machine-readable specification of data types for datasets will help address interoperability issues. Data types have typically been at the syntactical level such as integer, float and string, etc. in programming languages. The work presented in this paper is a model design(More)
Geoscience researchers are increasingly dependent on informatics and the Web to conduct their research. Geoscience is one of the first domains that take lead in initiatives such as open data, open code, open access, and open collections, which comprise key topics of Open Science in academia. The meaning of being open can be understood at two levels. The(More)
The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has(More)