CDOT Performance Data Business Plan - Cambridge Systematics

Appendices
A. Additional Data Collection
Recommendations
During the data collection phase within a data program, it is important to take
into account the following considerations:
Collect Accurate and Consistent Location Reference Data. Make sure that
performance data is collected with location referencing information that
allows it to be mapped and integrated with other data sources. There are
many efforts underway within CDOT to address this. Further
standardization in this area will help CDOT to better integrate and share
business data within the agency.
Put Data Quality Controls in Place. Location and temporal validity and
integrity control systems for data elements must be compatible. For example,
when collecting data from multiple pieces of equipment, by way of multiple
methods or from multiple sources, consistency of the measurement must be
assured. Data from surveillance systems are often faulty or missing because
of errors in the surveillance system (e.g., loop detector errors, communication
drops between loops and traffic management centers (TMC), etc.). It is
important that reliable detector diagnostic tools be in place to check the data
for accuracy and also to fill missing data based on reliable statistical
procedures. Data quality also is an area of focus for CDOT. For example, the
Division of Transportation Development (DTD), Traffic Analysis Unit (TAU)
has very specific data quality controls in place for the collection, analysis and
reporting of traffic data. Similar/ related quality assurance could be more
standardized within CDOT.
Data Should Facilitate Integration. Data should be used to facilitate
integration of information available from multiple systems. This includes
collecting and formatting data at an acceptable precision level that allows for
easier integration of data across systems. The current lack of standards for
data management within CDOT may be leading to redundancies in data
collection and in fact may be hindering integration.
Data Formats. It is essential that all data are provided in electronic format. It
is quite common that static data pertaining to network characteristics are in
non-electronic form (maps, drawings, as built plans, or aerial photos), which
makes it difficult and time consuming to code electronically. Such data
should ideally be available electronically in previously developed simulation
tools, GIS tools, or other software packages.
Open Data and Open Standards. The availability of privately owned,
continuously collected data has the potential to improve evaluations but is
likely to increase the complexity of conducting evaluations. This issue calls
Cambridge Systematics, Inc. A-1