Augmenting a conceptual model with geospatiotemporal annotations

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

While many real-world applications need to organize data based on space (e.g., geology, geomarketing, environmental modeling) and/or time (e.g., accounting, inventory management, personnel management), existing conventional conceptual models do not provide a straightforward mechanism to explicitly capture the associated spatial and temporal semantics. As a result, it is left to database designers to discover, design, and implement - on an ad hoc basis - the temporal and spatial concepts that they need. We propose an annotation-based approach that allows a database designer to focus first on nontemporal and nongeospatial aspects (i.e., "what") of the application and, subsequently, augment the conceptual schema with geospatiotemporal annotations (i.e., "when" and "where"). Via annotations, we enable a supplementary level of abstraction that succinctly encapsulates the geospatiotemporal data semantics and naturally extends the semantics of a conventional conceptual model. An overarching assumption in conceptual modeling has always been that expressiveness and formality need to be balanced with simplicity. We posit that our formally defined annotation-based approach is not only expressive, but also straightforward to understand and implement.

Original languageEnglish (US)
Pages (from-to)1324-1338
Number of pages15
JournalIEEE Transactions on Knowledge and Data Engineering
Volume16
Issue number11
DOIs
StatePublished - Nov 2004

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Semantics
Environmental geology
Personnel

Keywords

  • Data semantics
  • Database design
  • Geospatial databases
  • Semantic model
  • Temporal databases

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Information Systems

Cite this

Augmenting a conceptual model with geospatiotemporal annotations. / Khatri, Vijay; Ram, Sudha; Snodgrass, Richard Thomas.

In: IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 11, 11.2004, p. 1324-1338.

Research output: Contribution to journalArticle

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