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NSSI Information Exchange Workshop
Breakout Session Worksheet 5
What are the desirable attributes of a North Slope information and analysis system?
Who owns it?
Who runs it?
Who has access to it?
What are the standards?
What should be in it?
What are appropriate spatial and temporal scales?
What is the general architecture?
What kind of QA is needed?
How do we handle public versus proprietary data?
Others?
What is the general architecture?
Security will be an issue
Develop infrastructure that insures connectivity
Server communication
Enterprise level capability, 24-7 operation
MOU that agrees to a certain connectivity protocol
Need to be able to Process & query, data from a single environment
WEB MAPPING SERVICE protocols are becoming available (at geography.net)
Major data layer issues
Store data in most disaggregated form possible so that it can be aggregated later
Disjunction in data due to technology changes, overlapping methods used to translate data until new method is
established
Disaggregated data needs to be digested to be usable (hard copy data reports)
Establish a protocol for data summaries so everyone does not have to process the data
System Manager limit access to qualified users (public and private environments/access)
Single Point of Entry/Portal on one website, links from agencies ie. NSSI.org?
META DATA
Meta data is retained and published to determined reliability of the data (parameters for search, where & who)
Document the data obtaining steps
FGDC meta data standards for mapping/imagery
Develop a standard Meta vocabulary to obtain data (synonyms)
Should have Good search (key word) capability
Should have Good data sets
Should have Good Suite of tools (meta data service- used to find data, ESRI meta data explorer)
DATA SHARING
Issues with data sharing/contribution
How will lines drawn between agencies, ngo’s and others on data access, what are the limits, why?
List available reports and data and how to access them
Generally if a final report is published then the data should be available
Licensing will be an issue, i.e AEROMAP will generally restrict their imagery beyond primary user
What kind of QA is needed?
Data quality categories to aid usability (Coding)
Should be the scientist or contributor responsibility
Data center should have control over the integrity of the meta data (minimal meta data standard), the
responsibility of the principal investigator should be the QA/QC issues
Build tools for principal investigator
What are appropriate spatial and temporal scales? Just slope wide data sets?
Localized studies can help you understand synoptic data sets
Start with the data sets that it is intended to inform ( for management)
Temporally focus forward to standardize techniques
Focus on relevant data sets not all data/standards for new studies
Use historical data on a selective basis