Geography Reference
In-Depth Information
et al.
1991
; Chrisman
1984
; Hunter
1999
). In industrial sense, quality is basically
the level of fulfilment of the production process, it is i.e. a function of
non-substantial qualities such as completeness and consistency influenced by pro-
duction process (Veregin
1998
). Based on the definition of quality derived from
encyclopaedic dictionary (Weber and Buttenfield
1993
), quality is viewed as a
distinguishing property allowing to distinguish whether the given property has
positive or negative character. Based on this division, two other terms can be
derived—accuracy and mistake. If quality has a positive character, it could be
measured by the likeliness to the chosen model or reality, and the result is the
already mentioned term accuracy. On the other hand, negative approach is mea-
sured by discrepancy, i.e. mistake. From the point of view of geoinformatics, there
is a number of other views at the definition of quality of spatial data, because quality
is always related to a range of data characteristics. Individual definitions thus
usually reflect various views of the terminology of the notion itself and differ
from author to author.
From the beginning of the development of quality of spatial data, this field has
been a key subdiscipline of geoinformatics. It is considered to be of great impor-
tance both in the field of academic workplaces and in governmental and industrial
organizations. The quality of spatial data has been the topic of many conferences
and seminars and international activities (e.g. AGILE, GEOIDE, NCGIA and
others). However, the whole discipline, with regard to uncertainty, deals with the
above-mentioned problem, i.e. the disunion of used definitions and inaccurate
terminology. The stated can be demonstrated by an example where representatives
of governmental institutions and scientists working in academic environment are
asked to define “data quality” and “uncertainty”. It is very likely, that differing and
ambiguous answers will be given. The problem lies in the community of people
dealing with the quality of spatial data and uncertainty. In scientific articles,
professional reports and studies, it is very problematic to identify various concepts
that are called the same, or same concepts bearing differing names. As stated in the
preceding chapters, notions like uncertainty, mistake, accuracy, ambiguity and their
interpretation always reflect the scientific field from which the author using the
terminology is coming from. From the point of view of quality and uncertainty of
spatial data, in this interpretation, a division into two different communities of
people dealing primarily only with quality or uncertainty can be traced. Each of
these groups goes to their “own” conferences such as International Symposium on
Spatial Data Quality or International Symposium on Spatial Accuracy Assessment
in Natural Resources and Environmental Sciences. However, information and
opinions are usually not
interchanged between these two groups (Devillers
et al.
2010
).
