Information Technology Reference
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Fig. 2.
Data Model of Area Studies
created, used, discovered etc.) might be the only quantitative attributes which can be
used to identify and retrieve resources. These are backgrounds why spatiotemporal
attributes together with traditional bibliographic attributes are essential in area
informatics especially in “Knowledge Creation” phase in the Figure 1.
Figure 2 shows the data model proposed by the H-GIS [9], which is developed to
give an overall view of relationships between data types and tools necessary for area
studies. In this model, all objects (materials, events, phenomena etc.) are expressed as
dots distributed in a 3D space spanned by three axes.
The subject axis groups objects by subjects (i.e., vocabularies/meanings), which
corresponds to bibliographic databases. An RSS is the typical database system
developed by the H-GIS, which will be explained in Chapter 3. A retrieval operation
extracts objects that are distributed within a particular section on the axis (i.e., a
particular subject). Zoom-in operation narrows down subjects using narrower
vocabularies listed in thesauruses. Zoom-out is the opposite operation. Data mining is
to discover some relationships among objects by vocabularies.
The spatial axis arranges objects by place, which corresponds to maps. A mapping
operation extracts objects that are distributed within a particular section on the axis
(i.e., a particular area). A 2D plane spanned by the subject axis and the spatial axis
includes maps about particular subjects and areas (subject maps). These maps
correspond to “layers” of GIS tools. HuMap is a GIS tool developed by the H-GIS,
which will be explained in Chapter 4. Zoom-in operation enlarges a particular area of
a map in great detail. Zoom-out is the opposite operation. Data mining is to find
patterns from distributions of objects on a map such as randomness, coherency,
periodicity and decrement from the center to periphery, and to find patterns between
maps such as coexistence and transition.
