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18-Geom-A7 Geospatial Information Systems · December 2018

Question 2 of 15: Conceptual, logical and physical models

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 2: Conceptual, logical and physical models (10 marks)

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.

Designing a geospatial database proceeds through three levels of abstraction — an established database-design sequence (mirroring the ANSI/SPARC external–conceptual–internal idea) — moving from how humans understand the world down to how a machine stores it. Each level is derived from the one above by adding implementation detail.

Conceptual model reality → entities Logical model data structures / schema Physical model implementation on disk increasing implementation detail →
Figure — the three modelling levels of geospatial database design, refined left-to-right.

1) Conceptual model. Defined as a high-level, software-independent abstraction of the part of reality to be captured: it identifies the phenomena of interest (rivers, parcels, roads, elevation), decides whether each is a discrete object or a continuous field, and states the entities, their attributes and the relationships among them — without any concern for how they will be stored. Produced by requirements/domain analysis with users. Represented by entity–relationship diagrams, UML class diagrams or concept sketches.

2) Logical model. Defined as the translation of the conceptual model into a specific data-modelling paradigm — vector (point/line/polygon, with or without topology), raster, or the relational/object schema — still independent of any particular product. It fixes feature classes, geometry types, attribute fields, keys, domains and the relationships/constraints between tables. Produced by mapping each conceptual entity to a data structure and normalizing the tables. Represented by a relational schema, OGC simple-feature type definitions, or a logical schema diagram.

3) Physical model. Defined as the actual implementation of the logical schema in a chosen GIS/DBMS: the real tables, file formats (geodatabase, shapefile, GeoTIFF), spatial indexes (R-tree, quadtree), storage layout, coordinate system, tolerances and precision on the storage medium. Produced by the DBA/GIS analyst instantiating the schema in the software and tuning it for performance. Represented by the populated database itself — the physical files, tables and indexes. Together the three form a top-down refinement from meaning to bytes.