Informatics Research at NSIDC: Themes
This simplified notional diagram shows the relationships between several of the informatics projects at NSIDC. Whenever possible, the informatics team works to integrate solutions into the NSIDC infrastructure.
Here we highlight some of our research projects and results, organized by theme.
Challenge: Researchers want to use a single interface that knows about all the available data relevant to their problem.
Approach: Cyberinfrastructure that makes it easy to build portals tailored to community needs.
Solution: Arctic Data Explorer
The Arctic Data Explorer lets you search multiple repositories with one click. Here you will find diverse Arctic research data from many domains.
The BCube team is exploring how software components that mediate interactions between existing and emerging information systems can help scientists be more effective and productive by making it easier for them to discover, share and access data. This includes continuing development of web crawling capabilities to discover advertised data and services no matter where they are on the web (e.g., OpenSearch, OGC W*S, OPeNDAP, etc.); and developing and extending simple tools that allow researchers to advertise their data so those data can be added to portals and made discoverable.
Challenge: Researchers and stakeholders want to be able to use their own preferred tools to work with data.
Approach: Make data and systems more adaptable to popular tools.
Extend the variety of tools (e.g., ArcGIS, R, etc.) with which the BCube broker can directly interface
Solution: Proper curation of data to enable machine access and easier format conversions.
Research: User research
Determine what tools and services NSIDC users are most clamoring for and attempting to implement those.
Challenge: Different vocabularies can be an obstacle to finding data.
Approach: Develop ontologies and semantic technologies.
Enhance and test semantically enabled query expansion in the BCube broker.
Extend and connect cryospheric ontologies to the terminologies used by Arctic residents in their native languages.
Solution: Semantic enabling
Ensure that NSIDC’s glossary of cryospheric terms is semantically enabled so that it can be used in the above efforts.
Challenge: Interdisciplinary research may require varying levels of data and information,
Approach: Develop data summaries, data visualizations, and expert commentary and analysis.
Challenge: Interdisciplinary reserach entails challenges with integrating data within and across domains and durability of data systems.
Approach: Develop true data curation systems for dealing with multiple forms of data and that support technology change into the future.
Solution: Data Conservancy System software
NSIDC participated in the development of the DCS and is implementing an instance of the DCS to curate ELOKA data.
Challenge: Arctic data repositories are not equipped for the complexities of managing and curating social science data
Approach: Develop approaches to working with different resource types (e.g., audio, video, transcripts) and with issues in working with human subjects.
Solution: Exchange for Local Observations and Knowledge of the Arctic (ELOKA)
Exchange for Local Observations and Knowledge of the Arctic – ELOKA is working toward providing the support to local and traditional knowledge research, and community-based observations and monitoring, which are key components to any Arctic Observing Network (AON). ELOKA will provide a data management and networking service for community-based research that keeps control of data in the hands of community data providers, while still allowing for broad searches and sharing of information.
Challenge: Data sharing is not yet a normative behavior among scientists.
Approach: Connect data and data sharing to research and publication processes
Data citation policies
Stable data identifiers (DOIs)
Data management planning services
Data management education and outreach efforts
Challenge: Current data storage and access frameworks do not support cross-cutting queries and analysis.
Approach: Investigate alternate storage frameworks. Implement web services and applications for data subsetting and extraction.
Research: Data Rods
The Data Rods project proposes to create a new data structure for rapid retrieval, filtering, and analysis of massive multi-modality data sets.