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Paleoinformatics Goals

 

 

Machu Picchu

Technologies and methodologies include areas such as:

  • Digital field data acquisition methods including photogrammetry and related high density survey, and geophysical systems
  • Satellite, aerial and terrestrial remote sensing Analysis and management systems including statistical systems, simulation/modeling systems, geographic information systems, database management and related areas such as ontologies, semantic web, data mining and interoperability
  • Tomography
  • Representation and interpretation systems including landscape, architectural and object visualization, animation and other related 3D methods

 

The term paleoinformatics anticipates the continuing process of digital convergence as previously isolated methodologies become increasingly integrated through computational research and the parallel view that digital mensuration and other recording provides an environment that allows seamless movement of data and information from basic research through public interpretation. The definition of paleoinformatics used here subsumes that of “archaeological informatics” and “computational archaeology” (c.f. Burenhult G. and J Arvidsson 2002, Huggett and Ross 2004). Our usage differs from the only other existing use of paleoinformatics by MacLeod and Guralnick (2000) who restrict its use to the paleontological arena.

The scale of mensuration and analysis range from (small scale) regional landscapes to (medium scale) sites through (large scale) structures to (very large scale) objects, including architectural elements, artifacts and skeletal elements. Previously, different, and frequently incompatible, methods and data recording are applied in each of these classes. Because field data and other primary measurement will be digital - concern must be given to the transition of these data through analysis and interpretation and digital archiving. Integration of multiple data streams requires interoperability and the development and use of appropriate semantic structures and ontologies.

As Snow and his co-authors have made clear (2006), there are a wide range of differing terms (semantics) and classification structures (ontologies) in use across investigations. A major research area in computational investigations is the development of the “semantic web,” which is defined as a universal medium for the exchange of machine-readable data. The challenges of the data of paleoinformatics represent a vehicle to investigate important basic research areas in computer science and will provide excellent graduate opportunities to address this issue. Similarly photogrammetric and high density survey (e.g. laser scanning) based measurement of ancient architecture and objects is essential to both understanding the past and preserving the record. Applying these approaches, however, also represents important methodological challenges in the photogrammetric field and thus provides a high quality setting for graduate training in the photogrammetric and survey sciences. There are equivalent graduate education opportunities in each of the collaborating disciplines. Being able to integrate data using information technology on all levels will lead the students (and faculty) to synergistically work together, building a whole that is much greater than the sum of its parts.