Geographic information systems and digital libraries: Issues of size and scalability

The term "scalability" has specific connotations in Geographic Information Systems (GIS) that conventionally relate to monitoring and predicting growth of geographic phenomena. A family of computational models has been developed to predict changes in structure associated with changes in size. These models have been applied in physical science, social science, and cartographic science to study growth and may assist in monitoring the growth of digital libraries as well. As the size of the digital library increases, challenges for data organization and collection maintenance tasks will also increase. However, the rate of increase may not be in linear proportion to library size. At some critical scales, existing procedures will fail and new procedures must be implemented to accommodate further growth. Allometric principles may be applied to estimate these critical scales. Three aspects (data volume, indexing, and metadata recordation) will be discussed in the context of implementing and maintaining a digital library containing spatial data archives distributed across local or global electronic networks.published or submitted for publicatio

Multiple Representations—NCGIA Research Initiative 3, Closing Report

This report describes the results of NCGIA Initiative 3 on Multiple Representations, carried out in the period 1988-1990. Use of the term "Multiple Representations" refers to changes in geometric and topological structure of a digital object that may occur with the changing resolution at which that object is encoded for computer storage, analysis, and depiction. The implications of changing levels of resolution are important considerations in cartographic representations that figured prominently in the research reviewed in this report

Multiple Representations—NCGIA Research Initiative 3, Closing Report

This report describes the results of NCGIA Initiative 3 on Multiple Representations, carried out in the period 1988-1990. Use of the term "Multiple Representations" refers to changes in geometric and topological structure of a digital object that may occur with the changing resolution at which that object is encoded for computer storage, analysis, and depiction. The implications of changing levels of resolution are important considerations in cartographic representations that figured prominently in the research reviewed in this report

NCGIA Research Initiative 8 (Formalizing Cartographic Knowledge): Scientific Report for the Specialist Meeting (95-15)

This report is a summary of the Specialist meeting for NCGIA Research Initiative 8 entitled "Formalizing Cartographic Knowledge". The Specialist Meeting was held in Buffalo New York, 24-27 October 1993 to discuss knowledge representation and formalization issues relating to automation of cartographic processes. The four research topics given high priority are to formalize the language of cartographic elements and to standardize definitions of GIS processing operations, to implement formalized mechanisms to evaluate mapping system design, to impose more rigorous structure on the process of eliciting cartographic knowledge, and to embed cartographic knowledge into spatial data models and spatial data processing models

NCGIA Research Initiative 8 (Formalizing Cartographic Knowledge): Scientific Report for the Specialist Meeting (95-15)

This report is a summary of the Specialist meeting for NCGIA Research Initiative 8 entitled "Formalizing Cartographic Knowledge". The Specialist Meeting was held in Buffalo New York, 24-27 October 1993 to discuss knowledge representation and formalization issues relating to automation of cartographic processes. The four research topics given high priority are to formalize the language of cartographic elements and to standardize definitions of GIS processing operations, to implement formalized mechanisms to evaluate mapping system design, to impose more rigorous structure on the process of eliciting cartographic knowledge, and to embed cartographic knowledge into spatial data models and spatial data processing models