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Cyberinfrastructure Topics

Several topics are being investigated to improve cyberinfrastructure for science, research, and education. Selected cyberinfrastructure topics pertinent to scientific research and engineering are described in the following paragraphs.

Collaborative environments can help individuals to create and display information in an information space that can be shared among collaborators and other interested individuals.

Cybersecurity efforts include the development of tools and procedures to ensure the integrity of scientific and technical data (STD) and related information resources and to provide assurances for the trustworthiness of the cyberinfrastructure and its information resources.

Data integration includes the development of software and methodologies to combine data from various resources and to facilitate analysis using measures from individual resources or combinations of resources.

Data interoperability improvements include the development of standards, languages, and protocols that can enable data exchange between services. Examples of general protocols for interoperability include the Open Archives Initiative - Protocol for Metadata Harvesting (OAI-PMH), the Search/Retrieve URL and the Search/Retrieve Web Services (SRU/SRW) protocols. The Open Geospatial Consortium has been developing standards for the interoperability of geospatial data.

Data visualization activities include the development of protocols, software, and services for representing data graphically. Visual representations of data can support analysis and the development of educational products that inspire interest.

Digital preservation efforts include the development of systems and protocols for storing and describing data and research-related information to enable future access and use. Examples include digital repository systems, standards, and protocols that address cultural, organizational, and technical constraints and that enable the description, storage, conversion, and representation of various types of data and information.

Grid computing improvements enable multiple devices that are connected on a network to contribute to services and resources for representing and analyzing data.

Semantic Web developments improve capabilities for machines to exchange information that enables discovery and includes the development of ontologies and languages for describing scientific data and information.

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