Quality Data, How do I recognize it?
Database Attributes
When defining the minimum acceptable accuracy levels in a GIS for the database attributes it
can be broken down into two categories that include valid values and data content. Although
both have a direct impact on the integrity of the database each one has its own means of
validation. Valid values can be verified through automatic editors while data content needs to be
verified through manual edits. The cost of editing and verifying may have a direct impact on
what acceptable levels will be established for each category
Valid Values
Valid values are described as a set of values that can populate a database field with no
exceptions. Any values entered into these specified database fields that fall outside of this
predefined set of valid values is deemed in error. Some examples of sets of valid values would
be:
- Conductor size: 6, 2, 4, 1/0, 4/0, 336, 500, etc.
- Pipe size: 1, 2, 4, 6, 8, 10, 12, etc.
- Numeric values: any numeric value characters
- Standardized street name suffixes: St, Wy, Cr, Ave, Hgwy, etc.
- Standard Defaults: any value that is a standard default value in a particular field, this can
also include “nulls” and or blank fields.
Valid Values should have a minimum acceptable accuracy standard of 100%
Data Content
Data content on the other hand is much more difficult to verify. It requires a manual effort to
physically edit the values populated in each database field and make a decision as to if it is the
correct value as compared to the original source documents used to capture the information. The
value populated in the field may even be a valid value but is it the correct valid value?
Because of the effort involved in verifying every field in every attribute table the minimum
acceptable accuracy standard for data content is generally set at 98%.
Spatial Placement
Spatial placement within the GIS refers to where the objects within the GIS are in reference to
their actual locations in the real world. Spatial placement can be broken down into two areas of
reference. These two areas are absolute placement and relative placement. Although these two
areas can define the location of the same object or objects they are quite different.
Absolute Placement
When discussing absolute placement within a GIS, it refers to where an object is located in
reference to its location in the real world according to its control coordinate system. This control coordinate system is generally the Global Positioning System (GPS). To verify an object’s
absolute accuracy, the (X,Y) coordinate of the object in the GIS should be the same (X,Y)
coordinate value when checked in the field. Although the absolute placement of an object may
be the most desirable means of placing an object in a GIS, the cost of doing so, along with the
issue of the absolute accuracy of the landbase within the GIS, makes it the most difficult to
maintain and therefore the least common method used. Many times the absolute position of an
object or its GPS coordinates are stored as an attribute value of that object and used for various
engineering applications while the object is positioned in the GIS using relative placement
techniques.
The accuracy standards for placing objects within a GIS by their absolute locations can be
anywhere from ± .5 feet to ± 5’.
Relative Placement
Relative placement is the most common means of positioning objects within a GIS. Relative
placement refers to placing an object in relative position to the objects around it. This can be
done by visual placement or by using standard offsets. An object may not be in its absolute
position but it is correctly offset from other objects within the GIS. Poles are the correct distance
from each other; they are in the correct property lot, valves are the correct distance from
pavement edges, spans of wires and or pipes are the correct lengths and correctly offset from
landmark features.
The accuracy standards for placing objects within a GIS by their relative locations can be
anywhere from ± .5 feet to ± 10’.
Map Aesthetics
Of all of the components of a GIS that accuracy standards need to be applied to, map aesthetics
is by far the most difficult to quantify. The difficulty comes in to play because you really won’t
know what looks good until you see it and several people will have several differing opinions as
to what looks good. It seems like no matter how detailed graphic placement specifications for
rotation, offsets and size may be there are always instances that are the exception. Because map
aesthetics are the first thing a user may see it is important that the map products be visually
appealing with all objects being legible and easily decipherable. Consideration must be given to
the amount of time and resources that could be spent in continually repositioning objects to
achieve a higher level of aesthetics that may or may not affect the overall performance of the
GIS and its applications.
The accuracy standards for map aesthetics are generally established at 98% of the objects must
be correctly placed in regards to rotation and/or offset with minimal or no overstrikes for
displayed text.
Age of Data
Although the age of the data is a direct correlation to the sources used to create the data, it is still
important to have up to date data in the GIS to facilitate acceptance and therefore use of the GIS
throughout the user community. If the system users do not have confidence that the data they are
accessing is up to date and useful to them in making their appropriate decisions they will not rely
on it and as an end result not use the GIS. Every effort must be made to use only the most recent sources available to capture the objects included in the GIS. In addition, an aggressive
maintenance and update process must be in place to ensure the continued integrity of the
database.
The age of the data within the GIS should be no older than 6 months out of date.
Data Completeness
Even though all the data captured in the GIS is accurate and meets the minimum accuracy
standards, has all of the data from the original sources been captured? Data completeness
addresses this concern. By comparing the information object by object to the data depicted on the
original sources an accurate evaluation can be made. Although this is a manual process, the
effort spent to verify data completeness can be worthwhile. Should several critical objects not
have been captured, like a number of transformers, vales or switches, it could have a serious
impact on the effectiveness of the GIS applications.
The minimal acceptable accuracy standard for data completeness should be 98%
The following bullets summarize the minimal acceptable standards for each of the data quality
categories.
