Archived Data System --> Archived Data User System:
archived data products

Definitions

archived data products (Information Flow): Raw or processed data, meta data, data catalogs and other data products provided to a user system upon request. The response may also include any associated transaction information.

Archived Data System (Source Physical Object): The 'Archived Data System' collects, archives, manages, and distributes data generated from ITS sources for use in transportation administration, policy evaluation, safety, planning, performance monitoring, program assessment, operations, and research applications. The data received is formatted and tagged with attributes that define the data source, conditions under which it was collected, data transformations, and other information (i.e. meta data) necessary to interpret the data. The archive can fuse ITS generated data with data from non-ITS sources and other archives to generate information products utilizing data from multiple functional areas, modes, and jurisdictions. The archive prepares data products that can serve as inputs to federal, state, and local data reporting systems. The 'Archived Data System' may reside within an operational center and provide focused access to a particular agency's data archives. Alternatively, it may operate as a distinct center that collects data from multiple agencies and sources and provides a general data warehouse service.

Archived Data User System (Destination Physical Object): 'Archived Data User System' represents the systems users employ to access archived data. The general interface provided allows a broad range of users (e.g. planners, researchers, analysts, operators) and their systems (e.g. databases, models, analytical tools, user interface devices) to acquire data and analyses results from the archive.

Included In

This Triple is in the following Service Packages:

This triple is associated with the following Functional Objects:

This Triple is described by the following Functional View Data Flows:

This Triple has the following triple relationships:

Communication Solutions

Solutions are sorted in ascending Gap Severity order. The Gap Severity is the parenthetical number at the end of the solution.

Selected Solution

US: ADMS - Secure Internet (ITS)

Solution Description

This solution is used within Canada and the U.S.. It combines standards associated with US: ADMS with those for I-I: Secure Internet (ITS). The US: ADMS standards include upper-layer standards required to implement interfaces with an archived data management system. The I-I: Secure Internet (ITS) standards include lower-layer standards that support secure communications between ITS equipment using X.509 or IEEE 1609.2 security certificates.

ITS Application Entity
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Security
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TransNet
Access

Internet Subnet Alternatives
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Note that some layers might have alternatives, in which case all of the gap icons associated with every alternative may be shown on the diagram, but the solution severity calculations (and resulting ordering of solutions) includes only the issues associated with the default (i.e., best, least severe) alternative.

Characteristics

Characteristic Value
Time Context Historical
Spatial Context Regional
Acknowledgement True
Cardinality Unicast
Initiator Destination
Authenticable True
Encrypt True


Interoperability Description
Regional Interoperability throughout the geopolitical region is highly desirable, but if implemented differently in different transportation management jurisdictions, significant benefits will still accrue in each jurisdiction. Regardless, this Information Flow Triple should be implemented consistently within a transportation jurisdiction (i.e., the scope of a regional architecture).

Security

Information Flow Security
  Confidentiality Integrity Availability
Rating High High Low
Basis Data may include sensitive information which should not be casually viewable. As many requests could be quite large, the cost of compromise will be corresponding
ly high.
Since the whole point of an archived data request is some sort of data analysis, the contents of that data must be intact or the effort is wasted. Such requests can be for very large data sets, the effective cost of which is high. While the data sets are large, requests should be infrequent, and can be managed with interruptions in service.


Security Characteristics Value
Authenticable True
Encrypt True