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Proceedings ArticleDOI

Investigative analysis across documents and drawings: visual analytics for archaeologists

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TLDR
Indiana Finder is presented, an interactive visualization system that supports archaeologists in the examination of large repositories of documents and drawings that provides visual analytic support for investigative analysis such as the interpretation of new archaeological findings, the detection of interpretation anomalies, and the discovery of new insights.
Abstract
With the invention and rapid improvement of data-capturing devices, such as satellite imagery and digital cameras, the information that archaeologists must manage in their everyday's activities has rapidly grown in complexity and amount. In this work we present Indiana Finder, an interactive visualization system that supports archaeologists in the examination of large repositories of documents and drawings. In particular, the system provides visual analytic support for investigative analysis such as the interpretation of new archaeological findings, the detection of interpretation anomalies, and the discovery of new insights. We illustrate the potential of Indiana Finder in the context of the digital protection and conservation of rock art natural and cultural heritage sites. In this domain, Indiana Finder provides an integrated environment that archaeologists can exploit to investigate, discover, and learn from textual documents, pictures, and drawings related to rock carvings. This goal is accomplished through novel visualization methods including visual similarity ring charts that may help archaeologists in the hard task of dating a symbol in a rock engraving based on its shape and on the surrounding symbols.

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Visualization of Cultural Heritage Collection Data: State of the Art and Future Challenges

TL;DR: This survey reviews information visualization approaches to digital cultural heritage collections and reflects on the state of the art in techniques and design choices, and contextualizes the survey with humanist perspectives on the field and point out opportunities for future research.

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Geographic Visualization in Archaeology

TL;DR: This paper reviews the use of GIS in archaeology from a geographic visualization (geovisual) perspective and examines how these methods can broaden the scope of archaeological research in an era of more user-friendly cyber-infrastructures.
Journal Article

A holonic multi-agent system for sketch, image and text interpretation in the rock art domain

TL;DR: The architecture of a holonic multi-agent system for rock art interpretation and the results achieved within the “Indiana MAS” project are presented and the way Indiana MAS holons cooperate in order to provide correct interpretations of ambiguous shapes is discussed by means of an example based on hypotheses recently advanced by archaeologists.
Proceedings ArticleDOI

Petroglyph Recognition Using Self-Organizing Maps and Fuzzy Visual Language Parsing

TL;DR: A new algorithm for recognizing petroglyphs within scenes composed of several engraved figures, which combines an unsupervised recognizer, Self-Organizing Maps (SOM), with a fuzzy visual language parser.
References
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Illuminating the Path: The Research and Development Agenda for Visual Analytics

TL;DR: This is the book form of the Research and Development Agenda for Visual Analytics to be published by IEEE in 2005.
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Exploratory search: from finding to understanding

TL;DR: Research tools critical for exploratory search success involve the creation of new interfaces that move the process beyond predictable fact retrieval.
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Making Sense of Sensemaking 1: Alternative Perspectives

TL;DR: This essay examines sensemaking from various perspectives to see if the authors can separate the things that are doable from the Things that seem more like pie-in-the-sky.
Journal ArticleDOI

ThemeRiver: visualizing thematic changes in large document collections

TL;DR: The ThemeRiver visualization depicts thematic variations over time within a large collection of documents and uses a river metaphor to convey several key notions, allowing a user to discern patterns that suggest relationships or trends.
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