Data management and maintenance are continuous processes used to make sure that data is current, consistent, and reasonable. Quality assurance (QA) ensures that the data collection method can be repeated and provide consistent or similar data results every time. Quality control (QC) is an evaluation method that looks at data to determine if it is reasonable and consistent.
For example, QA for traffic data collection to study traffic on a four-lane road requires the tribal planner to set up traffic counters and loops across all lanes for four or five consecutive weekdays. QA also includes periodic checking of traffic counters to make sure that they are working and to note any broken equipment or odd-looking data. Once the traffic data is collected, the QC process is initiated, which looks at the full set of data to determine if the recorded data is within a reasonable range of what is expected. If for example, no traffic is counted for a full day or if the traffic count is significantly higher or lower on one counter the QC process would highlight that day's data as not being credible and it would not be used to tell the story of traffic on the four-lane road.
Data and the things it describes are constantly changing. It should be reviewed, updated, revised, or discarded to ensure that it is:
Data becomes "bad" when it is too old, no longer reflects current conditions, or is somehow flawed by the collection or analysis methods used. If bad data is detected, the tribal planner must decide if the data set can be salvaged by, for example, adding new data to the data set, or if the best strategy is to start over with a more rigorous data collection effort.
Each data set has its own unique update and review cycle based on how frequently it changes. Data that does not change rapidly, such as the condition of the roadway surface, might require only annual or periodic review; whereas, for the data that changes continuously, such as traffic volume, more frequent collections may be needed. The tribal planner might want to set up criteria and schedules for reviewing the different types of data. Table 3 provides an example of a data review and update timetable.
Table 3 Sample Data Review and Update Timetable
|Time Frame||Data Set||Data Item|
|As needed, when new data is available||System Inventory||Road mileage|
|System Inventory||Sidewalk and pedestrian paths|
|System Inventory||Bike paths|
|Weekly, Monthly, Seasonally||System Inventory||Land use zones|
|Traffic||Hourly traffic counts|
|Traffic||Total miles traveled by all vehicles over a given time period|
|Motor Fuel||Gallons purchased|
|Annually||Bridge||Bridge structural inspection|
|Bridge||National Bridge Inspection Standards Rating|
|Pavement||Condition survey (every three years)|