Cyberinfrastructure

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Description: Research environments that support advanced data acquisition, data storage, data management, data integration, data mining, data visualization and other computing and information processing services distributed over the Internet beyond the scope of a single institution. In scientific usage, cyberinfrastructure is a technological and sociological solution to the problem of efficiently connecting laboratories, data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge.

Projects:
DTDI Project LogoDeep Time Data Infrastructure (DTDI)
Principal Investigator: Peter Fox
Description: Earth’s living and non-living components have co-evolved for 4 billion years through numerous positive and negative feedbacks. Yet our ability to document, model, and explore these complex intertwined changes has been hampered by a lack of data synthesis and integration from many complementary disciplines—mineralogy, petrology, paleobiology, geochronology, proteomics, geochemistry, and more. The rise of oxygen exemplifies the co-evolution of rocks and life, and underscores both the tantalizing opportunities and technical challenges of deciphering transient characteristics of Earth’s storied past.
MBVL Project LogoMarine Biodiversity Virtual Laboratory (MBVL)
Principal Investigator: Stace Beaulieu, Peter Fox, Heidi Sosik, and David Mark Welch
Description: This research effort brings together computational and information scientists, oceanographers and microbiologists to develop a Marine Biodiversity Virtual Laboratory (MBVL). In addition to research investigations of marine ecosystems, the Virtual Laboratory provides a platform for education via student diversity programs at the three institutions. The important learning opportunities will be two-fold for students: (1) to learn about, model, and make predictions for biodiversity in natural systems, and (2) to be exposed to working in an interdisciplinary team that includes both natural scientists and computer scientists.
Nanomine LogoOntology-Enabled Polymer Nanocomposite Open Community Data Resource (Nanomine)
Principal Investigator: Cate Brinson, Wei Chen, Deborah L. McGuinness, and Linda Schadler
Description: Our evolving semantics=driven data resource, named NanoMine, is an open access, user friendly, living, growing, data resource for the polymer nanocomposites community that is scalable and enables improved understanding of processing – structure - property relationships and thus facilitates faster nanocomposite design and insertion into advanced applications. By bringing together the data that is scattered throughout the public literature and private files and creating a protocol for recording and tagging data, this resource is an unprecedented compilation of information that is accessible. Tools within the resource allow users to visualize complex data, analyze images from their work, and design new polymer nanocomposites materials. For NanoMine to realize broad community acceptance and address scientific questions at the forefront of technology, it marries cutting edge cyber infrastructure with a robust set of data and tools.
TWC schema.org Project LogoTWC Schema.org Vocabulary Development (TWC_Schemas)
Principal Investigator: Jim Hendler
Co Investigator: Joshua Shinavier
Description: schema.org provides a collection of schemas — html tags — that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google, Yahoo! and Yandex rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Since early 2012 researchers at TWC RPI have been working with government and research data providers to define vocabularies for expressing the structured data that powers their web sites, using on-page markup based on schema.org vocabularies. In particular, we developed the schema.org/Dataset extension, a concise vocabulary that extends schema.org for describing datasets and data catalogs. Current work includes applying Dataset to scientific datasets and developing new extensions for use by Web Observatories