Subcommittee on Data

 

Chair:

Gregory Slater, Director of Planning and Preliminary Engineering, Maryland State Highway Administration


 

Data Subcommittee Efforts

Core Data Principles Development
The SCOP Data Sub-Committee leadership has refined a set of core principles for transportation data.  The principles have been developed and vetted by the sub-committee, the CTPP oversight board (data community), and US DOT data leadership.  The principles have been vetted through SCOP, and key state and federal transportation data people.  Finalizing and publicizing the principles, with the intent of using them to guide our future work and approach is the ultimate goal. Here is the final draft of the Core Data Principles:
 

Principle 1 - VALUABLE: Data is an asset—Data is a core business asset that has value and is managed accordingly.

Principle 2 - AVAILABLE: Data is open, accessible, transparent and shared—Access to data is critical to performing duties and functions, data must be open and usable for diverse applications and open to all.

Principle 3 - RELIABLE: Data quality and extent is fit for a variety of applications—Data quality is acceptable and meets the needs for which it is intended.

Principle 4 - AUTHORIZED: Data is secure and compliant with regulations—Data is trustworthy and is safeguarded from unauthorized access, whether malicious, fraudulent or erroneous

Principle 5 - CLEAR: There is a common vocabulary and data definition—Data dictionaries are developed and metadata established to maximize consistency and transparency of data across systems.

Principle 6 - EFFICIENT: Data is not duplicated—Data is collected once and used many times for many purposes.

Principle 7 - ACCOUNTABLE: Decisions maximize the benefit of data—Timely, relevant, high quality data are essential to maximize the utility of data for decision making.

For a more in depth look at each principle, keep reading...

Principle 1: Data is an asset

Rationale—Data is a core industry asset that has measureable value and is managed accordingly. Accurate, timely data is critical to accurate, timely decisions. Transportation agencies already manage many of their physical assets: roads, bridges, signs, lights, etc. Data is no different and must be treated like other physical assets. Data is the foundation of our decision-making, so we must also carefully manage and maintain data to ensure that we know what we have and where it is, can rely upon its accuracy, and can obtain it when and where we need it. Where possible, data should be archived to maintain historical records.

Implications—Treating data as the asset that it is saves money, effort and resources.  When data is appropriately handled it can have a long life with many uses beyond its original one, and serve projects as yet unplanned.

Principle 2: Data is open, accessible, transparent, and shared

Rationale—The value of data is increased when it can be used with other data and in a variety of applications. Users must have access to the data critical to their duties and functions. Wide access to data leads to efficiency and effectiveness in decision-making, and affords timely response to information requests. Using data must be considered from an enterprise perspective (across the organizations or across multiple organizations) to allow access by a wide variety of users. Transportation agencies at all levels of government (federal to state to local) hold a wealth of diverse data sets, but it is often stored in different databases that are incompatible with each other or difficult to find. Timely access to accurate data is essential to improving the quality and efficiency of decision-making. It is less costly to maintain timely, accurate data and then share it, than it is to maintain duplicative data in multiple locations or processes. Shared data will result in improved decisions since we will rely on fewer sources of more accurate and timely managed data for decision-making. Sharing is also necessary to triangulate on subjects that may not be measured directly, and allows for serendipity. Insights often come from bringing fresh eyes to data.

As transportation organizations work with more stakeholders and external partners, it is essential that data be shared. Making data electronically available will result in increased efficiency when existing data entities can be re-used. It is more effective to de-protect transportation data than it is to over-protect.

Implications—Agencies are increasingly under in informal mandate to "do more with less."  Sharing data is a key step in executing this mandate. Accessible data will ultimately reduce burden on staff time as data becomes more accessible.

Principle 3: Data quality is fit for purpose

Rationale—Data quality is acceptable and meets the need for which it is intended. Data that is collected, produced, and reported must be fit for purpose. That is, of sufficient accuracy and integrity proportional to its use and cost of collection and maintenance. Data is used in all areas of the transportation decision-making process from planning to design to operations to performance management. Furthermore, it is increasingly being used externally by citizens and customers to inform their personal decisions, and by stakeholders to assess the aggregate performance of a transportation organization. Significant human and system resource is consumed in the collection, manipulation and dissemination of data whether of high quality or not, so it is essential that the most effective use of public funds is achieved through appropriately directed attention to data quality and the procedures to realize quality. Additionally, data must be archived appropriately to preserve both its usefulness and the historical record. When possible, data should be spatially oriented. Data quality increases as the application of the data increases. Data that has spatial orientation or attribution can easily be used in GIS systems. When data assets can be analyzed in a spatial context, not only can a greater analysis be completed in terms of geographic context, but also the data and any analysis results can be more easily communicated via mapping and other formats more applicable to public understanding.

Implications—When data is fit for purpose appropriate cost decisions are made in its collection and use.  In cases where a rough sketch is appropriate, appropriate data collection and use may follow.  Where large programs, investments, or systems are being developed and vetted, those data must be fit for that purpose.  Data precision is matched to the task at hand.

Principle 4: Data is secure and compliant with regulations

Rationale—Data is trustworthy and is safeguarded from unauthorized access, whether malicious, fraudulent or erroneous. Open sharing of information and the release of information via relevant agreement must be balanced against the need to restrict the availability of classified, proprietary, and sensitive information.

Implications—When data is secure and appropriately regulated there is greater trust and confidence in its use.

Principle 5: There is a common vocabulary and data definition

Rational—Both unstructured and structured data must have a common definition to enable sharing of data. However, data must not be compromised below the use of its original purpose.  Commonality may take the form of relations, bridges and crosswalks between definitions

Implications—A common vocabulary will facilitate communications, enable dialogue to be effective and facilitate interoperability of systems, however, utility must not be compromised.

Principle 6: Data is not duplicated

Rationale— Development of information services should be made available to multiple users and stakeholders and is preferred over the development of information and data silos which are only used for a single purpose or user.

Implications—Duplicative capability is expensive and propagates conflicting data. It also goes against a policy of sustainability in the use of data and the infrastructure resources required to maintain the data, such as computer servers and data warehouses.

Principle 7: Decisions maximize the benefit of data

Rationale—The purpose of data collection is to help support the decision-making process. Users of the data, as well as information derived from the data, are the key stakeholders in the data collection and analysis process. The data is being collected to address a certain policy goal or objective. In order to ensure information management is aligned with the purpose, users must be involved in the different aspects of the information environment. The decision makers, managers, and the technical staff responsible for developing and sustaining the information environment need to come together as a team to jointly define the goals and objectives of the data collection processes.

Implications—Resources are limited. Maximizing existing resources is essential.

 
AASHTO Data Guidebook

A scoping study is underway under the auspices of the Transportation Research Board National Cooperative Highway Research Program quick response tasks (NCHRP 8 - 36).  The task (129) Scoping Study to Establish Standards and Guidance for Data for Transportation Planning and Traffic Operations Purposes was selected in May, 2013.  The work is expected to commence in late 2014.

National Data Advisory Council
The Data Sub-Committee Leadership is developing a framework for a national Data Advisory Council.  This body will include State, Regional and National representation and look at issues of data needs.  It will maintain a contact list of key state, federal and regional data players. Future efforts of the SCOP Data Sub-Committee are to revamp and make useful the SCOP Data Subcommittee website- and to look at the feasibility of developing and supporting a National Transportation data Clearinghouse- an AASHTO based source for transportation data.
 
 
Data Subcommittee Related Efforts
 
FHWA National Household Travel Survey (NHTS)
 
The NHTS serves as the nations inventory of personal travel and represents the only authoritative source of national data on personal travel behavior, including purpose of the trip, means of transportation, trip length, day of week and month of year, number of people on a trip and a host of other trip making characteristics.  The last NHTS was conducted in 2010; the 7th in a data series which started in 1969.  In the past, AASHTO has passed resolutions urging the US DOT to provide sufficient resources to make the NHTS a regular and sustained data resource for transportation planning.  The TRB Policy Study on travel recommends improved, expanded and sustained collection of household travel data, using a continuous survey process. Currently TRB has convened a three year task force to   discuss proposed survey modifications and explore potential impacts on various transportation data user communities.
 
Improving FHWAs Ability to Assess Highway Infrastructure Health
 
The FHWA Office of Asset Management has initiated a project to define a consistent and reliable method of assessing infrastructure health with a focus on pavements and bridges on the Interstate Highway System.  The project is also being designed to develop tools for providing FHWA and state DOTs ready access to key information that will allow for a better and more complete view of infrastructure condition and health nationally.  The data collection and analysis portion of the project has started to obtain pavement and bridge condition data on a three-state pilot study corridor and compare it to state provided HPMS and National Bridge Inventory data.  The pilot study corridor selected for the study is I-90 in South Dakota, Minnesota and Wisconsin.  AASHTO SCOP staff are monitoring the project, with state representatives from Minnesota, Missouri, North Carolina, Tennessee, Washington and Wisconsin.  Contact: Nastaran Saadatmand, FHWA or Matt Hardy, AASHTO.
 
FHWA Traveler Analysis Framework
 
FHWA has initiated a project to calculate long-distance travel trip tables for all passenger modes.  In May 2011, a draft methodology paper describing the derivation of long-distance passenger travel for the base year 2008 was circulated for review and comment.  States interested in more information should contact Daniel Jenkins, FHWA Office of Policy Information, at daniel.jenkins@dot.gov
 
FHWA Roadway Safety Data Partnership
 
FHWA has a new roadway safety data partnership project underway to assess how states collect, analyze, manage and expand data for comprehensive highway safety planning.  A data questionnaire assessment is currently being piloted in Montana, Massachusetts, North Carolina and Minnesota.  The assessment includes questions on roadway inventory and safety data management systems, analytical methodologies, data governance, data management and interoperability.