Designing the Archive for SHRP 2 Reliability and Reliability-Related Data (2014) / Chapter Skim
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13 Preparatory Analysis The project team performed a thorough preparatory analysis task to get more familiar with the data archiving state-ofpractice and understand the available content management technologies that can be used for L13A. This task included review of the L13 report (Section 3.1)
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14 3.1.2 Findings 3.1.2.1 SHRP 2 Management Perspective One of the primary objectives of the Reliability Archive was to allow users to find and validate the research results from relevant SHRP 2 projects and to refine and build on research results in the future. Another primary objective of the Reliability Archive was to preserve research project data.
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15 performance measures. They need to quickly find the conclusions of each project, executive summaries, and presentations.
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16 • Service-oriented architectures (SOA) ; and • Virtualization.
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17 The visioning and filtering process that the L13 research team went through led to the conceptual solution framework as shown in Figure 3.2. Using this framework, the research team proposed a number of alternative system solutions, which are described next.
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18 object replication to ensure their security and integrity over time.
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19 An April 1998 report to the FHWA's Office of Highway Policy Information is largely dedicated to ADUS's "institutional issues for implementation" (Margiotta 1998)
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20 Table 3.2. Needs of ADUS Stakeholders (continued)
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21 Safety planners and  administrators Safety management  systems Areawide safety monitoring; studies of  highway and vehicle  safety relationships Exposure (typically VMT)   derived from short-duration  traffic and vehicle classification counts; traffic conditions  under which crashes  occurred must be inferred.  Police investigations, the  basis for most crash data  sets, performed manually.
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22 practice and to equivalent solutions available from ADUS systems. The table was compiled by Margiotta and published in Margiotta (1998)
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23 The PORTAL system covers the Portland-Vancouver metropolitan region. The current system (as of the time when the literature review was conducted)
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24 3.2.3.3 CATT Lab, Maryland The University of Maryland Center for Advanced Transportation Technology Laboratory (CATT Lab) builds, operates, and maintains the transportation data archive for the Washington metropolitan area and other states (University of Maryland 2012)
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25 Traffic Visualization System (AITVS) that provides real-time highway monitoring capabilities via comprehensive visualization components.
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26 data and for operational support. The Backbone Project also serves transit and traveler information programs within Washington State DOT (WSDOT)
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27 3.2.3.8 Minnesota DOT RTMC The Minnesota Department of Transportation (MnDOT) built the original transportation management center in 1972 to manage the freeway system in the Twin Cities metropolitan area.
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28 cameras in the municipality of Delft are also being archived. Sample camera locations are shown in Figure 3.14.
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29 Figure 3.14. Map of camera locations from Regiolab's website.
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30 accidents, vehicle breakdowns, traffic signal status, current electronic road pricing rates, and work zones (Figure 3.18)
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31 Archived Data Type Ontology, a well-established standard for the handling of archive data. Table 3.3 summarizes the archive data levels suggested by CODMAC.
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32 Table 3.3. Archived Data Levels Level Description Example Formats Level 0 Raw data, including raw traffic  data such as volumes and  speeds Raw digital data and  imagery Level 1 Georeferenced data, such as  speed associated with a  specific route and direction Individual records,  processed images Level 2 Derived variables at the same  resolution and location as  the Level 1 source data from  which the variables are  derived Individual records,  processed images Level 3 Variables mapped on spacetime grid scales Imagery depicting the  changes in time  and/or space of  variables Level 4 Model output or results from  analyses of lower-level data  (i.e., variables derived from  multiple measurements)
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33 Table 3.4. Sample of Existing Online Data Archives Focused on Research Archive Domain Size Increase Data Levels Real-Time/ Near-Real-Time?
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34 UCLA Social Science Data Archive http://www.sscnet .ucla.edu/issr/da/ Social Sciences >500 GB a 0–5 None None News posting, integration with Twitter  and Facebook Search for data  only Heavily hyperlinked between  multiple  universities U.S. Census Bureau http://factfinder2 .census.gov/faces/ nav/jsf/pages/ index.xhtml Social Sciences >250 GB a 4–5 None Many data sets can  be displayed on a  map.
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35 Table 3.5. Data Archival Technologies Tool Application Appropriateness (scale of 1 to 10, 10 being highest)
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36 3.4.1.3 Nuxeo Nuxeo is a free ECM system written in Python that includes functionality, such as document management, social collaboration, case management, and digital asset management capabilities. Nuxeo is similar in scope, scale, and cost to Alfresco and was considered a viable alternative.
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37 (REST) and Simple Object Access Protocol (SOAP)
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38 lessons that could be drawn from the review of the ADUS guidelines: • Ensuring that institutional issues like privacy concerns, liability, and confidentiality of privately collected data were taken care of in the data provided by SHRP 2 project teams; and • Incorporating training and outreach in the project. The key to successful outreach will be to show that ADUS systems help perform common tasks faster and more easily and accurately.
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