Browsing by Subject "Data management"
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Item Chukchi Sea environmental data management in a relational database(2013-05) Yang, Fengyan; Maidment, David R.Environmental data hold important information regarding humanity’s past, present, and future, and are managed in various ways. The database structure most commonly used in contemporary applications is the relational database. Its usage in the scientific world for managing environmental data is not as popular as in businesses enterprises. Attention is caught by the diverse nature and rapidly growing volume of environmental data that has been increasing substantially in recent. Environmental data for the Chukchi Sea, with its embedded potential oil resources, have become important for characterizing the physical, chemical, and biological environment. Substantive data have been collected recently by researchers from the Chukchi Sea Offshore Monitoring in the Drilling Area: Chemical and Benthos (COMIDA CAB) project. A modified Observations Data Model was employed for storing, retrieving, visualizing and sharing data. Throughout the project-based study, the processes of environmental data heterogeneity reconciliation and relational database model modification and implementation were carried out. Data were transformed into shareable information, which improves data interoperability between different software applications (e.g. ArcGIS and SQL server). The results confirm the feasibility and extendibility of employing relational databases for environmental data management.Item The Long Tail of hydroinformatics : implementing biological and oceanographic information in hydrologic information systems(2012-12) Hersh, Eric Scott; Maidment, David R.; Bonner, Timothy; Dunton, Kenneth; Gilbert, Robert; Hodges, Ben; McKinney, DaeneHydrologic Information Systems (HIS) have emerged as a means to organize, share, and synthesize water data. This work extends current HIS capabilities by providing additional capacity and flexibility for marine physical and chemical observations data and for freshwater and marine biological observations data. These goals are accomplished in two broad and disparate case studies – an HIS implementation for the oceanographic domain as applied to the offshore environment of the Chukchi Sea, a region of the Alaskan Arctic, and a separate HIS implementation for the aquatic biology and environmental flows domains as applied to Texas rivers. These case studies led to the development of a new four-dimensional data cube to accommodate biological observations data with axes of space, time, species, and trait, a new data model for biological observations, an expanded ontology and data dictionary for biological taxa and traits, and an expanded chain-of-custody approach for improved data source tracking. A large number of small studies across a wide range of disciplines comprise the “Long Tail” of science. This work builds upon the successes of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) by applying HIS technologies to two new Long Tail disciplines: aquatic biology and oceanography. In this regard this research improves our understanding of how to deal with collections of biological data stored alongside sensor-based physical data. Based on the results of these case studies, a common framework for water information management for terrestrial and marine systems has emerged which consists of Hydrologic Information Systems for observations data, Geographic Information Systems for geographic data, and Digital Libraries for documents and other digital assets. It is envisioned that the next generation of HIS will be comprised of these three components and will thus actually be a Water Information System of Systems.Item Session 1H | Getting to know you: Results of the Texas Data Repository User Survey(2022-05-23) Chan-Park, Christina; Sare, Laura; Waugh, Laura"The Assessment Committee of the Texas Data Repository (TDR) Steering Committee conducted a survey in Spring 2022 of TDR users. The TDR uses the Dataverse platform for publishing and archiving datasets (and other data products) created by faculty, staff, and students at Texas higher education institutions and hosted by the Texas Digital Library. There are currently nine participating member institutions. The purpose of the survey is to gauge overall user experience with the TDR in order to identify areas for improvement and/or future integrations with a focus on how the platform is used for research. The survey was administered to over 1000 registered users of the TDR including researchers from member institutions as well as any researchers that created accounts to deposit or download data. In addition to general questions about using the TDR, users were asked about their experience creating collections, depositing data, and downloading data. In this presentation, we report on the findings of this study.