Improving Findability and Relevance of Transportation Information: Volume I—A Guide for State Transportation Agencies, and Volume II—Background Research (2017) / Chapter Skim
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V o l u m e I I Background Research
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C o n t e n t s V o l u m e I I Background Research II-3 Chapter 1 Introduction II-3 1.1 Project Overview II-4 1.2 Document Overview II-5 Chapter 2 Current Practices for Improving Findability II-5 2.1 Overview II-5 2.2 Literature Review II-11 2.3 Findability Practices -- DOTs II-18 2.4 Findability Practices -- Other Organization Types II-22 Chapter 3 Framework for Improving Findability II-22 3.1 Framework Development Process II-22 3.2 Final Framework II-27 Chapter 4 Pilot Demonstration II-27 4.1 Pilot Objectives II-27 4.2 Identification of Pilot Agencies II-29 4.3 Summary of Pilot Activities II-30 4.4 Level of Effort for the Pilot II-34 4.5 Transferability and Scalability of the Pilot II-36 Chapter 5 Conclusions and Future Research Needs II-36 5.1 Conclusions II-38 5.2 Future Research Needs II-41 References II-42 Appendix Pilot Findability Report II-43 A.1: Pilot Overview II-44 A.2: Assessment II-49 A.3: Content Collection II-54 A.4: Solution Development II-68 A.5: Test and Evaluation II-75 Annex 1: Pilot Classification Rule Descriptions II-84 Annex 2: Example Scenarios Using Faceted Search Design II-90 Annex 3: Evaluation Metrics
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II-3 C h a p t e r 1 1.1 Project Overview Research Objectives The objective of this research was to improve state department of transportation (DOT) information findability by (1)
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II-4 Improving Findability and relevance of transportation Information 1.2 Document Overview Volume II of NCHRP Research Report 846 provides a high level summary of the project methodology and deliverables. The balance of Volume II is organized as follows: • Chapter 2 documents the information gathering activities and summarizes practices for improving findability.
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II-5 C h a p t e r 2 2.1 Overview The initial substantive research task involved a review of "successful practices for ensuring findability of mission-critical information in public and private sector organizations," leading to the development of an initial framework for ensuring findability. To accomplish this objective, the research team conducted a practice review involving a literature search, telephone surveys with five state DOTs, and documentation of prior research team project experience with findability projects outside of the state DOT community.
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II-6 Improving Findability and relevance of transportation Information and media creation management (see Table II-1)
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Current practices for Improving Findability II-7 • Information has a life cycle. A full life cycle view of information is needed to ensure findability -- and successful content management efforts encompass the creation, tagging, conversion, publication and retirement/culling processes.
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II-8 Improving Findability and relevance of transportation Information • A variety of approaches can be taken for the design of content classification and tagging methods. There is no single best way; the approach should be designed to fit the need: – Taxonomies can be helpful in situations for which findability can be enhanced via a hierarchical breakdown or tree structure of content (e.g., locating construction project information applicable to project phases, and tasks within phases)
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Current practices for Improving Findability II-9 • Leverage available technology for information storage and retrieval. • Establish categorization schemes for data and information management.
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II-10 Improving Findability and relevance of transportation Information • People search, by role (e.g., traffic engineer for City X) or by area of expertise.
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Current practices for Improving Findability II-11 Figure II-3 shows a simplified business process model developed as part of the Ohio DOT enterprise architecture study. Similar to the Kansas DOT value chain, it offers a way to associate the agency's information resources with key business activities.
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II-12 Improving Findability and relevance of transportation Information • The Mississippi DOT • The Illinois DOT • The Colorado DOT The interview was divided into the following sections: • Basic information about the agency (e.g., number of employees, system size)
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Current practices for Improving Findability II-13 systems and practices. In some instances, they consulted with others.
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II-14 Improving Findability and relevance of transportation Information elements, and ensuring searchability of content across SharePoint sites. There are more than 5 million documents in the system.
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Current practices for Improving Findability II-15 warehouse, a physical library staffed by professional librarians, use of SharePoint for document sharing and collaboration, use of ProjectWise for engineering document sharing, and deployment of a GIS tool providing access to widely used geospatial data. The DOT also noted that they are piloting a tool called Varonis for security management and file utilization tracking.
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II-16 Improving Findability and relevance of transportation Information • SAP Content Server • Data warehouse • Web-based content management system (e.g., Plone) • Custom applications (e.g., for right-of-way management, project management)
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Current practices for Improving Findability II-17 • Avoid information loss due to lack of organized information management. • Protect investment in costly plans/studies and make sure they can be found.
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II-18 Improving Findability and relevance of transportation Information • Identify where full text search capability is sufficient and where additional effort to invest in taxonomy development and tagging is worth the cost. • Improve email and archived records findability.
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Current practices for Improving Findability II-19 the need for collaboration between central groups and distributed groups (e.g., field offices) and the need for a dedicated team working together to plan and implement improvements.
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II-20 Improving Findability and relevance of transportation Information Organization Lessons and Success Factors U.S. Government Accountability Office (U.S.
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Current practices for Improving Findability II-21 • Second, for many search applications, having high quality metadata that is based on welldesigned taxonomies is essential for success. In most cases, the more metadata added, the better the search experience will be.
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II-22 C h a p t e r 3 3.1 Framework Development Process Based on the information gathering activities, the research team developed a preliminary framework for improving findability at DOTs. This framework recognized the complexity of improving findability in a DOT and the need for a multi-pronged approach involving: • Understanding information seeking behaviors and needs.
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Framework for Improving Findability II-23 a solution that can make a noticeable difference -- it is unlikely that resources for findability improvement will be allocated and sustained. A clear focus on meeting business needs and matching of solutions to needs is critical to making progress.
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II-24 Improving Findability and relevance of transportation Information • More re-use of information, less re-work. Employees who cannot easily ascertain whether something already has been done that they could build upon may end up "reinventing the wheel." The resulting re-work diminishes the value of agency investments to develop reports, studies, data sets, etc.
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Framework for Improving Findability II-25 5. Implementing "quick wins" (improvements can be easily accomplished with existing resources)
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II-26 Improving Findability and relevance of transportation Information Information Management Techniques Findability techniques related to information management include: • Document management systems and content management systems. Use of these systems offers a more structured and contained environment for content than the "Wild West" of shared file drives and email attachments.
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II-27 C h a p t e r 4 4.1 Pilot Objectives A pilot demonstration was undertaken to: • Test and validate concepts and methods for improving findability and relevance of transportation information. • Identify areas for refinements.
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II-28 Improving Findability and relevance of transportation Information The Virginia DOT Background: The Virginia DOT's Knowledge Management Office is responsible for ensuring findability of the agency's mission-critical content through enhancement of information management and classification methods. The DOT uses SharePoint 2010 for their corporate intranet.
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pilot Demonstration II-29 Needs: The Washington State DOT had an interest in leveraging the work completed to date in order to move forward with implementation of a findability solution in support of PDR information searches and potentially a broader set of findability use cases. Specifically, the agency wanted to validate the content type and asset taxonomies that were developed with users, improve them as needed, investigate practical approaches to creation and assignment of metadata, and develop strategies to integrate use of metadata with current (and future)
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II-30 Improving Findability and relevance of transportation Information run the indexing and categorization processes using the specifications and rules developed by the research team. Because the solution created as part of this project is based on specific commercial platforms, it is intended as a demonstration of capabilities only; it is not a packaged software product intended for distribution.
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pilot Demonstration II-31 Step Activities 2. Define the Target Scope Select Target Needs • After analysis, four categories of needs were identified to be addressed in the pilot: - Find a specific known document for a project (e.g., an estimate)
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II-32 Improving Findability and relevance of transportation Information 4. Develop the Solution Identify the Search Facets • Based on the search needs and the content analysis, the following search criteria were identified: content type, contract award amount (ranges)
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pilot Demonstration II-33 Table II-3. (Continued)
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II-34 Improving Findability and relevance of transportation Information The estimated total effort was about 700 hours across all team members. An approximate breakdown of this effort across the major pilot activities appears at the end of this section.
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pilot Demonstration II-35 for projects, districts, highway system categories, and so forth would need to be replaced with equivalent data. Interestingly, two of three rule sets for identifying types of work issues (i.e., drainage and weather-related issues)
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II-36 C h a p t e r 5 5.1 Conclusions DOT Business Drivers for Findability Based on the literature review, information gathering, and pilot activities conducted for NCHRP Project 20-97, a recognized need exists to improve findability of information within transportation agencies. Needs of greatest concern are efficient retrieval of information in response to FOIA requests, PDRs, and legal claims; and ensuring that employees can find current, authoritative versions of agency policies, manuals, guidance, and standards.
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Conclusions and Future research Needs II-37 implementation of a workable metadata strategy will be required to improve findability. Developing a workable metadata strategy means standardizing on an essential set of metadata elements that are (1)
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II-38 Improving Findability and relevance of transportation Information 5.2 Future Research Needs Future research would be beneficial in several areas: • Additional DOT pilots to validate, extend, and facilitate adoption of the findability practices developed in the initial pilot. • Investigation of machine learning techniques for auto-categorization of content.
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Conclusions and Future research Needs II-39 community. They do not, however, involve actual implementation or development of the techniques.
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II-40 Improving Findability and relevance of transportation Information utilities) to train the analytics software.
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II-41 Boiko, B., and E
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II-42 A p p e n d i x This appendix documents implementation of a findability pilot for the Virginia DOT and an analysis of the transferability of pilot results with the Washington State DOT. Three annexes providing additional details are included at the end of the appendix: • Annex 1: Pilot Classification Rule Descriptions • Annex 2: Example Scenarios Using Faceted Search Design • Annex 3: Pilot Evaluation Metrics and Description Pilot Findability Report
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pilot Findability Report II-43 A.1: Pilot Overview The research team conducted pilot activities at the Virginia DOT (VDOT) in order to demonstrate an application of the findability framework and potential benefits from findability improvements.
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II-44 improving Findability and Relevance of Transportation information Source: Adapted from figure in internal draft document from Kansas City DOT (2005)
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pilot Findability Report II-45 Construction Office staff wanted to find patterns across projects, District Construction staff primarily focused on locating information about specific projects. Interviews A 3-day site visit to VDOT was conducted during May 4–6, 2015, during which members of the research team met with Knowledge Management staff, construction staff from three districts, representatives of the central office Construction Division, and Information Technology staff responsible for the agency's content management/collaboration platform implementation, including search capability configuration.
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II-46 improving Findability and Relevance of Transportation information This included the following findings. More detail on a number of these findings is included in the "Content Harvesting, Analysis, and Conversion" section.
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pilot Findability Report II-47 Table II-A-1. Summary of VDOT Business Questions and Search Needs ID Business Question/Search Need Comments 1 Where was work actually done (for projects that do not have a single routefrom-to location)
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II-48 improving Findability and Relevance of Transportation information ID Business Question/Search Need Comments 8* Find construction documents based on one or a combination of: tax map parcel, project number/universal project code (UPC)
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pilot Findability Report II-49 The selected information access needs can be classified into four categories. These four categories serve to organize the pilot evaluation test cases described in the "Testing and Subjective Evaluation" section: 1.
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II-50 improving Findability and Relevance of Transportation information In addition to the three above content types, the research team elected to include a fourth type that would provide a user with general information about a construction project. Project profiles for each construction project were created utilizing information that was publicly available for download from VDOT's online dashboard, in the "Project Delivery" section.
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pilot Findability Report II-51 with fewer issues related to naming conventions which were more standardized given that the content was for a single project. There were some variations between the megaproject and the internal VDOT content.
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II-52 improving Findability and Relevance of Transportation information team opened each email and downloaded the relevant attachments. Although Smartlogic could be configured to search both email and attachment text, it would only be able to do so for attachments with searchable text.
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pilot Findability Report II-53 Document Length. Some documents were quite lengthy.
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II-54 improving Findability and Relevance of Transportation information Type of Work (e.g., Bridge Widening, Grade / Drain / Pave)
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pilot Findability Report II-55 The research team turned to content from the districts. The research team began by using a number of text analytics tools to mine this content for entities and noun phrases, and manually analyzing content for concepts and complex relationships.
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II-56 improving Findability and Relevance of Transportation information Table II-A-2. Semantic Model Facet Included Values and Value Sources Facet Source of Values Included Values Content Type Content Analysis Values limited to: Work Order Daily Work Report Source of Materials Project Profile Related to Work Order Contract Award Amount Project List Ranges of: Less than $500,000 $500,000 - $1,000,000 $1,000,000 - $5,000,000 $5,000,000 and above Contractors Text Mining of Content Variety District Project List (VDOT Master Data)
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pilot Findability Report II-57 Facet Source of Values Included Values Projects Project List Variety Road System Project List Values limited to: Interstate Primary Primary (Arterial) Rural Secondary Urban Various Routes Project List Variety Type of Work Project List Values limited to: Box Culvert Bridge Bridge Ordinary Maintenance Bridge Painting Bridge Repair (& Rehab)
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II-58 improving Findability and Relevance of Transportation information Facet Source of Values Included Values Wildflowers Work Issue Content Analysis; Adapted from Previous Work (Sun and Meng) 4 Values limited to:5 Drainage Issue Utilities Issue Weather Issue Work Order Categories Content Analysis; Work Order Category Lists in VDOT Content Values limited to: ADD (Additional work not originally planned)
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pilot Findability Report II-59 Figure II-A-3. Top-level semantic model categories.
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II-60 improving Findability and Relevance of Transportation information relationship of "is a child of" so that now our relationships are: Tim is a parent of Sarah Tim has a child. Tim is a parent of Sarah is a child of Tim.
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pilot Findability Report II-61 Term class Term subclass Relationship Class of terms relationship is with Relationship type Projects has contract ID equivalence has project ID short equivalence has UPC equivalence Involves route Route associative is project of District associative has road system type Road System associative has contract award amount Contract Award Amount associative has type of work: Type of Work associative Road System is road system Projects associative Routes has road UF6 equivalence is a roadway of District associative is part of project Projects associative Type of Work is type of work Projects associative Work Issue has work issue C-84 associative has work issue C-10 associative Work Order Category hierarchal is work order category C-10 associative Rule Development and Refinement The Smartlogic Semaphore – Classification Server tool includes text analytics features that allow for development and application of rules that improve search results over a simple full text search capability. This proprietary, commercial software served as the basis for the pilot efforts to demonstrate improved findability.
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II-62 improving Findability and Relevance of Transportation information that are unique to each subject area. The research team used these processes to create rules for tagging content for each element in the semantic model.
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pilot Findability Report II-63 cases, but in others, a considerable (and unpredictable) number of words separated "Category:" and "Plan".
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II-64 improving Findability and Relevance of Transportation information analytics (including entity extraction) supplemented this analysis to find additional terms and phrases to use in the rules.
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pilot Findability Report II-65 classification provided an indication that overly broad rules were capturing casual references to work orders in addition to work orders themselves. Another common technique starts with a small set of documents and achieves maximum recall and precision, then tests the rules against new and larger sets of documents.
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II-66 improving Findability and Relevance of Transportation information Faceted Search Design The research team built a simple search interface, with facets on the left and search results in the middle of the screen. The faceted search design allows users to explore the content and refine the search results by filtering through selected criteria.
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pilot Findability Report II-67 The pilot solution also includes a capability to browse facets at the outset instead of needing to type in a search term to start a search. This provides users with a starting point for the search if they are unsure of what search term to use.
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II-68 improving Findability and Relevance of Transportation information A.5: Test and Evaluation Rule-Based vs. Plain Vanilla FAST Search One component of the pilot evaluation differentiates between a rule-based search and a plain vanilla FAST search.
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pilot Findability Report II-69 The number of documents needed to find 10 relevant results (or in some scenarios, a number less than 10) allows the research team to compare the vanilla and rule-based search capabilities to find a set of documents.
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II-70 improving Findability and Relevance of Transportation information section heading language, which could increase recall. Similarly, a more complete application could examine if including rules for finding work issues in additional parts of the document would allow for increased recall while maintaining a high level of precision.
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pilot Findability Report II-71 with the main advantages in using the rule-based search derived from general findings discussed above.
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II-72 improving Findability and Relevance of Transportation information Transferability Analysis The final component of the pilot evaluation considers the transferability to other agencies of the findability solution and development process. While each findability solution should be driven by an information architecture that is tailored to the agency's situation, the general ideas behind the pilot setup contained in this report are transferable, including the logic behind the rules in Annex 1.
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pilot Findability Report II-73 for a utility issue tend to capture some of the materials listed in the change order. Improving the precision of these rules would require narrowing the language and adjusting the scope of the rules to avoid that content.
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II-74 improving Findability and Relevance of Transportation information based search applied to the WSDOT context and uses. Participants represented the following functions: Knowledge Management Records Management Risk Management Communications (website)
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pilot Findability Report II-75 Annex 1 Pilot Classification Rule Descriptions The following subsections provide descriptions of the rules used to classify documents. The actual rules used in the pilot were built using a programming language (as demonstrated in the example rule in Figure II-A-5)
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II-76 improving Findability and Relevance of Transportation information The first listed phrase is on all C-25 forms. This may not catch Source of Materials that are not on the official form, but it screens out referrals to Source of Materials in emails and daily work reports.
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pilot Findability Report II-77 District Find one of the following: 1) A project identifier, as defined in the "Project" rules 2)
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II-78 improving Findability and Relevance of Transportation information Materials Find: 1) A single mention of the material Each material is weighted at 1.0.
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pilot Findability Report II-79 2) Several mentions of a route preceded by "RTE" 3)
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II-80 improving Findability and Relevance of Transportation information For example, the phrase "abandoned gas line" could have the following matches: 1) A phrase score: "The design calls to remove the abandoned gas line" 2)
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pilot Findability Report II-81 25) "revise drainage" 26)
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II-82 improving Findability and Relevance of Transportation information 34) "utility situation" 35)
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pilot Findability Report II-83 28) "wet weather" 29)
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II-84 improving Findability and Relevance of Transportation information Annex 2 Example Scenarios Using Faceted Search Design This Annex provides examples of search scenarios. These examples include screenshots of the faceted search design, in order to illustrate the pilot tool that the research team built.
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pilot Findability Report II-85 2. It is also possible to search by entering the contract number ("R00018944C02")
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II-86 improving Findability and Relevance of Transportation information 4. Once selected, clicking on the magnifying glass begins a search and leads to a set of 14 results.
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pilot Findability Report II-87 5. There are 13 results.
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II-88 improving Findability and Relevance of Transportation information Scenario 2: Finding Assets Supplied by a Specific Manufacturer 1. This example will search for content from a specific sign manufacturer, Korman Signs.
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pilot Findability Report II-89 3. This can then be further filtered by any number of criteria to further refine the results.
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II-90 improving Findability and Relevance of Transportation information Annex 3 Evaluation Metrics The following subsections present test case evaluations for the four different categories of information access needs identified in the VDOT interviews. Each test case description is accompanied by a definition of relevancy and a set of steps for both the vanilla and rule-based searches.
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pilot Findability Report II-91 A second test case (Tables II-A-7a and II-A-7b) similarly anticipates that the user will recognize the document when reading it, and provides the criteria that the user is searching for a FHWA conceptual approval of work orders related to a drainage issue, in ".doc" format.
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II-92 improving Findability and Relevance of Transportation information Table II-A-8a. Relevancy Criteria and Search Steps: Work Order for a Virginia Beach Bridge Project Relevancy Vanilla Search Steps Rule-Based Search Steps 1)
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pilot Findability Report II-93 Table II-A-9b. Precision Metrics: Daily Work Reports for Contract ID V00014672C01 Precision Metric Vanilla Rule-Based Total number of results (excluding duplicates)
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II-94 improving Findability and Relevance of Transportation information search for document recall, finding 92% of all relevant documents in the top 30 results (compared to 15% in the vanilla search)
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pilot Findability Report II-95 Table II-A-12a. Relevancy Criteria and Search Steps: Work Orders for Project Number 0337122-F14 Relevancy Vanilla Search Steps Rule-Based Search Steps 1)
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II-96 improving Findability and Relevance of Transportation information Table II-A-13b. Precision Metrics: Source of Materials Forms for Project 0615-047-169 Precision Metric Vanilla Rule-Based Total number of results (excluding duplicates)
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pilot Findability Report II-97 In this evaluation, the vanilla search is able to find a set of daily work reports that the rule-based search fails to classify. Both have 100% precision, but the vanilla search has higher recall in this case.
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II-98 improving Findability and Relevance of Transportation information Table II-A-16b. Precision Metrics: Documents including Pay Item for Underdrain UD-2 Precision Metric Vanilla Rule-Based Total number of results (excluding duplicates)
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pilot Findability Report II-99 The vanilla search finds more documents, but is unable to classify them by road system. A high proportion of all projects are for primary roads, so the vanilla search performs fairly well; however, it would not perform as well for other road types.
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II-100 improving Findability and Relevance of Transportation information Table II-A-19a. Relevancy Criteria and Search Steps: Name Recognition of Contractor that Korman Signs Supplied Relevancy Vanilla Search Steps Rule-Based Search Steps 1)
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pilot Findability Report II-101 Table II-A-20b. Precision Metrics: Source of Materials Form with "Kormen" Signs Supplier Misspelling Precision Metric Vanilla Rule-Based Total number of results (excluding duplicates)
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II-102 improving Findability and Relevance of Transportation information Table II-A-22a. Relevancy Criteria and Search Steps: Work Orders Related to Route I-95 in Richmond District Relevancy Vanilla Search Steps Rule-Based Search Steps 1)
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pilot Findability Report II-103 Subjective Evaluation" section, the recall of the rule-based search that uses section headers could be increased using additional variations for a more complete application. Table II-A-23a.
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II-104 improving Findability and Relevance of Transportation information Table II-A-24a. Relevancy Criteria and Search Steps: Work Orders that Directly Reference the Work Issue Relevancy Rule-Based Search Steps 1)
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pilot Findability Report II-105 Table II-A-25b. Precision Metrics: Work Orders Related to Weather Issues Precision Metric Vanilla Rule-Based Rule-Based (Headings)
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II-106 improving Findability and Relevance of Transportation information Table II-A-26a. Relevancy Criteria and Search Steps: Daily Work Reports Related to Drainage Issues Relevancy Vanilla Search Steps Rule-Based Search Steps 1)
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pilot Findability Report II-107 As in the examples measured in Tables II-A-18b and II-A-20b, the rule-based search that uses the section headings again has 100% precision. However, the reduced recall is clear in this example, as the number of relevant documents found in this search is lower than the other rule-based search and vanilla search.
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II-108 improving Findability and Relevance of Transportation information Table II-A-28b. Precision Metrics: Work Orders with "CHAR" Work Order Category Precision Metric Vanilla Rule-Based Total number of results (excluding duplicates)
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Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FAST Fixing America's Surface Transportation Act (2015) FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012)
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TRA N SPO RTATIO N RESEA RCH BO A RD 500 Fifth Street, N W W ashington, D C 20001 A D D RESS SERV ICE REQ U ESTED N O N -PR O FIT O R G .
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