This guide recognizes that activities associated with the archiving and retrieval of ITS-generated data must satisfy two classes of considerations – technical considerations and institutional considerations. Many aspects of such processes are analytic ones that need to address and satisfy various mathematical, statistical, data base management, information technology, or other similar technical concerns. On the other hand, many aspects of such processes are ones that need to address and satisfy various intra-agency, intra and inter-organizational, management approaches, decision-making, public-private participation, public involvement, or other similar such institutional concerns. This technical-institutional duality usually must both be satisfied for a particular archiving or retrieval process to be efficient and effective. That may also require a change in focus of the group responsible for the ADMS work to meeting the needs of their customers. Thus, in planning, designing, or operating the functions and interfaces of an ADMS, appropriate technical and institutional approaches must often be explored concurrently in order to have an overall efficient and effective archiving or retrieval of ITS-generated data, or both. However, even though this guide gives importance to the institutional considerations when planning, designing, or operating an ADMS, this guide gives more weight and attention to the technical considerations of the functions and interfaces associated with an ADMS. This approach of focusing on function will give more latitude to institutions to be freer to arrange institutional matters on their own.

This Guide also deals in general with the questions of what data and information in particular should be considered for archiving as well as what data and information in particular should be considered for being retrieved. While more in depth consideration is to be given in the companion specifications, the following is a general characterization of what data and information should be considered for archiving. These include the following:

A structure of data storage based upon individual core data elements,

The data elements are stored in electronically readable media,

Documentation is included regarding the data structure and quality, and

Metadata is part of the archive relating to aspects such as the quality of the data and whether quality control adjustments have been made.

The particular original data sources and data elements that will be in an archive are expected to be unique to that archive. Which data sources and elements are used will depend upon a combination of the needs and requirements of potential users as well as the availability of particular data sources from other systems. For example, a particular ADMS may have some emergency management data on incident management responses, some traffic station sensor data from a traffic management subsystem, and some pavement temperature data from a roadway weather information system.

With regard to the what is to be retrieved, this guide recommends flexibility to provide for the needs of a diverse set of stakeholders. Some will want to retrieve short tabular summaries while others will want longer and more complex ones; some will want graphs and charts while others will want thematic maps of variations in the data. Accounting for different time periods and combinations of data and information quickly leads to an enormous range of possible data retrieval queries and approaches. While this guide does not recommend one retrieval approach being better than another because what is best will be very user specific, general guidance about the retrieval of data and information can be found in 10.16.8.

1.1 This guide covers desired approaches to be considered and followed in planning, developing, and operating specific ADMS for the archiving and retrieval of Intelligent Transportation Systems-generated data. The scope of this guide anticipates incremental or modular implementation of an ADMS, which over time and with a series of investment of resources will approach or exceed desired practice. However, it is recognized that programmatic constraints of time and budget resources do not always allow practitioners to follow a more desirable course of action and that during interim periods the ability to implement a particular fully functioning system may be less than desired.

1.2 The desired approaches described in this guide are foundational and are not intended to be all-inclusive. Users of this guide are allowed, and indeed encouraged, to exceed the desired practices in one or more of several ways. An example of one way is that to address and satisfy the particular needs and requirements of some of the intended users and stakeholders for a particular implementation may necessitate exceeding the desired practice. Another example is that some implementations may want to foster innovations and research into new methods and procedures related to the overall implementation of a particular ITS activity. Part of that may be the recognition that specialized archiving or retrieval processes, or both, would facilitate such innovations or research, or both. A third example is that some organizations may simply have more resources to invest in activities such as archiving and retrieval systems and may choose to have more quantities or higher quality of data and information available to their planning or operations units to use in their day-to-day activities.