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Data quality tool

1,600 bytes added, 06:45, 14 November 2010
address Seb's comments
The system, as currently envisioned, will be a web-based portal which will allow users to evaluate the quality of various data feeds through any modern, standards-compliant browser with an internet connection to CCIT servers. The interface will be primarily visual, allowing users to compare a number of metrics (described in more detail below) visually as well as numerically. At the current time, a comparison of at least one and at most two data sources will be possible, though the system will be designed in such a way that the latter restriction will not be permanent and could be lifted in the future.
In the spirit of modern and user-friendly web design paradigms, the system should be responsive and visually appealing. Exporting data (both in tabular and graphical format) for sharing via email or other means should be easy and not painful. The tool should be useful "as is" or "out of the box" but still allow a useful amount of customization to allow users to tailor it to their specific needs or application. More details on the user interface and program layout will be specified in a separate document. The system will be targeted primarily at CCIT researchers familiar with the different data feeds and models which are available. However, the user interface will be designed with less technical users in mind, so that (for example) it can be demoed live to transportation professionals.
Note that in general, the CCIT system contains two types of data feeds: travel time distributions (such as the FasTrack travel time system) and point-based speed/flow/density estimates. In the short term, the system will be designed with the latter group of feeds in mind. However, it should be architected in such a way that the addition of travel time feeds should be possible without much additional effort.
The data quality assessment tool should provide an easy-to-use interface to specify "correct" or benchmark values for each of the metrics, as the tolerable amount of, for example, GPS error depends on the specific application for which the data is being considered. Also, any feed available to the system should be usable as a benchmark for any metric (as long as it has the data to calculate it).
 
All metrics, whether direct or calculated, will generally be generated on-the-fly for each request. As such, the system does not require the use of a database for storing calculated data. If system usage is high enough that database load or performance become a problem, we should look into using [http://www.memcached.org memcached] for storing the calculation results. Since the results are transient, storing them permanently in a database does not make much sense.
 
It is possible that the system will allow users to flag specific, problematic data points or feeds. Since this feature adds the overhead of having to store this data in a manageable and useful fashion, it is not clear if this will be implemented in the initial release.
===Data-level metrics===
*Distribution of GPS errors (as reported by the recording device)
*Distribution of map-matching errors (as determined by MM mapmatching algorithms)
*Density of data (total number of points per link)
*Frequency of new data receipt (total per link)
*Data transmission delay (time difference between data recording and data storage on server; 2-step delay for TeleNav only: device→TeleNav server→CCIT server)
*Distribution of point location distance from link end (for city locations with traffic lights, provides ability to flag when most data points are not on the ends, since people should be waiting at lights)
All of these metrics should be filterable by time intervals, feed, device model (if available), location (specified as a network, polygon, or set of specific links), and unique device. This would allow for the analysis of derived metrics such as "density of data per unique device" or "distribution of point location from link end for the city of SF."
The value of information is defined as the degree to which the distribution of travel times from some model more closely resembles some "ground truth" distribution previously obtained. The difference between adding a single feed and multiple feeds is fairly self-explanatory: the former evaluates the value of information from adding a single feed to some baseline model, whereas the latter does the same but for more than one feed. Note that these are different metrics, because the improvement in the model output neither linear nor monotonically additive in the positive direction. As a result, certain feed combinations could actually worsen model performance, while other feeds which provide dramatic improvements individually may not add much when other feeds are added at the same time.
 
==Future directions==
For the future, the system should be able to accommodate these additional feed types.
 
===Travel time distributions===
For comparing travel time feeds, the system should provide metrics which are applicable to distributions of values instead of individual values. For example,
*The Wasserstein metric (comparison of distributions) (estimated travel time distribution vs. collected samples)
 
===Link-based feeds===
*Density of data (total number of points per link)
*Frequency of new data receipt (total per link)
*Distribution of point location distance from link end (for city locations with traffic lights, provides ability to flag when most data points are not on the ends, since people should be waiting at lights)
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