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18-Geom-A7 Geospatial Information Systems · December 2018

Question 9 of 15: Data–information–knowledge and decision-maker preference

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

Paper format. National Exams, December 2018 — 04-Geom-A7, Geospatial Information Systems. Closed book (one approved Casio or Sharp calculator permitted); duration 3 hours. Fifteen (15) questions are provided and any ten (10) constitute a complete paper; each question is of equal value (10 marks), so a complete paper totals 100 marks. Most answers are essay-format; clarity and organization count. All fifteen questions are solved below for completeness.

Reference texts (subject)

Longley, Goodchild, Maguire & Rhind, Geographic Information Systems and Science (4th ed.); P. Bolstad, GIS Fundamentals (5th ed.); Worboys & Duckham, GIS: A Computing Perspective (2nd ed.); Burrough, McDonnell & Lloyd, Principles of Geographical Information Systems (3rd ed.); de Smith, Goodchild & Longley, Geospatial Analysis; OGC Simple Feature Access (ISO 19125); ISO 19157 Geographic information — Data quality; ISO 19115 Metadata.

Question 9: Data–information–knowledge and decision-maker preference (10 marks — a 6, b 4)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

The three categories form the spatial version of the data–information–knowledge (DIKW) hierarchy, each adding context and value to the one below. Spatial data are raw georeferenced facts with no interpretation — coordinates, pixel/DN values, unprocessed observations. Spatial information is data that have been processed, organized and given context so they answer what and where questions — a thematic map, a query result, a computed suitability layer. Spatial knowledge is information synthesized with experience, domain rules and judgment into an understanding of patterns and relationships that supports action.

Spatial data raw facts Spatial information what / where Spatial knowledge patterns + preference Decision action / choice increasing context, value and interpretation →
Figure — the spatial DIKW hierarchy; a decision-maker's preference sits at the knowledge level, feeding the decision.

(a) Where a decision-maker's preference belongs. A decision-maker's preference or interest is not raw spatial data (it is not an observed coordinate or measurement) and it is not mere spatial information (it is not a processed map of what-is). It is applied understanding combined with values and priorities used to weigh alternatives — so it belongs in the Spatial knowledge category, the interpretive layer that sits just below, and directly drives, the decision itself. Preference expresses which patterns matter and why; that is knowledge, not data or information.

(b) Real-case justification. Consider siting a new hospital. The road network, a DEM and census population counts are spatial data. Running accessibility and proximity analysis to produce a travel-time and under-served-population suitability map is spatial information — it states what and where. When the health authority's planners decide that serving currently under-served neighbourhoods should be weighted more heavily than minimizing land cost, and read the suitability map through that priority to choose a site, they are applying spatial knowledge: their preference interprets the information and converts it into the decision. The same suitability map could yield different sites under different preferences, which shows preference operating at the knowledge/decision layer, not in the data or information beneath it.