LESSONS LEARNED IN CARTOGRAPHIC DATA MODELING IN SUPPORT OF GIS-BASED MAP PRODUCTION

A.R. Buckley, C. Frye

ESRI, Inc.

abuckley@esri.comn

 

Effective use of GIS for map production requires a well designed cartographic data model.  Cartographic data models are a formalization of the maps design stored in the features and attributes of a GIS database.  Cartographic data modeling requires a clear understanding of the maps that are being produced and in addition the software that is used to produce the maps.

 

An advantage of data modeling is that it requires us to think about the map design and the map making process. This results in the codification of the geographic features, attributes and processes that produce the desired cartographic product through specified software.  Arranging this information in a systematic form allows it to be shared and repurposed for other map making uses.  In some cases, it is possible to translate the cartographers thinking directly into the GIS data model; other times the requirements for the data model are more elusive because it is difficult to formalize how a cartographer completes certain tasks.  There are a number of reasons for this elusiveness, including the iterative and inexact nature of some map making tasks, the lack of attention historically given to codification of some map making tasks, difficulties in translating the task to its expression in a digital environment, and incomplete knowledge of the data and/or software used to complete the tasks.

 

We have learned much about how to design cartographic databases over the past ten years and more.  The lessons relate to translating the maps semantic model into a cartographic data model, informed data capture, database requirements for text placement and symbology, leveraging the database in order to maximize the software capabilities, and identifying opportunities for automated map production.  Some of the lessons we have learned include that: the maps an organization produces drive all aspects of cartographic data modeling; a complete inventory of the graphic marks on the maps is required to inform many aspects of the data model; semantic models do not have to be exhaustive in order to be complete; development of the cartographic data model must inform primary data compilation; the data model should allow you to store the closest representation of the final map in the database as possible.  We illustrate these lessons through multiple examples from various case studies.