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Data Modeling for Spatial Analysis • What is spatial analysis? – "a set of methods whose results change when the locations of the objects being analyzed change" • Methods for working with spatial data – to detect patterns, anomalies – to find answers to questions – to test or confirm theories • deductive reasoning – to generate new theories and generalizations • Inductive reasoning What is Spatial Analysis (cont.) • Methods for adding value to data – in doing scientific research – in trying to convince others • A collaboration between human and machine • How do we set up the framework for spatial analysis? – Data model to data structure A Georelational to a Geodatabase Model • coverage and shapefile data structures – homogenous collections of points, lines, and polygons with generic, 1- and 2-dimensional "behavior" • can’t distinguish behaviors – Point for a marker buoy, same as point for OBS • “smart features” in a geodatabase – lighthouse must be on land, marine mammal siting must be in ocean Purpose of Arc Marine, Arc Hydro and others • basic template for implementing GIS projects – input, formatting, geoprocessing, creating maps, performing analyses • basic framework for writing program code and maintaining applications – development of tools for the community • promote networking and data sharing through established standards “Generic” Marine Data Model User Group Data Model Project Data Model User Group Data Model Project Data Model User Group Data Model Project Data Model Inheritance Arc Marine Design Strategy Geodatabase Concepts • ESRI's new data object-oriented data model – objects, features, behaviors • Geodatabase – collection of feature classes/data sets, rasters, TINs – all data in relational tables – behavior is coupled with features through rules (object-orientation • Feature data set – Contains feature classes – defines topological role of features – has a coordinate system • Feature class – stored in a relational table – special field for geometric shape – geometric data incorporated into the database • Point, multipoint, segment, path, ring, polyline, polygon, • Zeiler p. 114 Geodatabase Feature Class Geometries ArcMarine Geodatabase Overall Geodatabase Feature Dataset Feature Class Table Relationship Class Modeling Process Conceptual Model Lists, flow diagrams, etc Real World Objects and relationships Logical Model Diagram in CASE Tool Physical Model Database Schema (Object state) Graphic courtesy of ESRI Data Model Levels Humanoriented Reality Conceptual Model Increasing Abstraction Logical Model Computeroriented Physical Model Specific Steps in Data Modeling (1) Conceptualize the user's view of data – what are the basic features needed to solve the problem? (2) Select the geographic representation – points, lines, areas, rasters, TINs (3) Define objects, features, and relationships – draw a UML diagram, specify relationships, “behaviors” (4) Match to geodatabase elements – Refine relationships, “behaviors” (5) Organize geodatabase structure, add data ( 1 ) User’s View of Data ( 1 ) User’s View of Data cont. (2) Select geographic rep. Steps in Data Modeling (1) Conceptualize the user's view of data – what are the basic features needed to solve the problem? (2) Select the geographic representation – points, lines, areas, rasters, TINs (3) Define objects and relationships – draw a UML diagram, specify relationships, “behaviors” (4) Match to geodatabase elements – Refine relationships, “behaviors” (5) Organize geodatabase structure, add data Unified Modeling Language • Entity-relationship diagrams • Design methodologies, diagram notations • UML – Not a design methodology – Just a diagrammatic notation based on methods – Endorsed by leading software and database companies • HTML