HDNS-I: Infrastructure for Knowledge Linkages from Ethnography of World Societies

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The goal of this project is to greatly enhance the value of an existing ethnographic database of world cultures to users by improving their ability to search by meaning rather than words, and providing tools for visualizing and analyzing their results. This project will add semantic tags and data-mining functions with associated computer services to enhance eHRAF World Cultures, presently containing about 750,000 pages from 6,500 ethnographic documents covering over 330 world societies over time. Since its inception in 1949, the Human Relations Area Files (HRAF) has developed and transformed information systems to facilitate the efficient retrieval of information on cultures of the world so that researchers from many different disciplines could arrive at better understanding of human behavior in all its variety. New semantic and data mining infrastructure developed by this project will assist in determining universal and cross-cultural aspects of a wide range of user selected topics, such as social emotion and empathy, economics, politics and use of space and time. The database can serve to examine the range of possibilities for human thought, knowledge, belief and behavior with respect to real-world problems faced today, such as: climate change; violence; disasters; epidemics; hunger; and war. Examining how and why cultures vary in similar circumstances is critical to improving policy, applied science, and basic scientific understandings of the human condition. Such knowledge is extremely valuable in understanding an increasingly globalized world. This project will develop advanced methods of working with text that can be applied from an extensible framework that deploys tools for analysis and retrieval. This services framework will be available for beginners and advanced researchers. Some methods can be applied in areas as far afield as AI and robotics, making AI solutions more human. Pattern extraction and linguistic analysis will be applied through AI tools to define a flexible logic for the contents of the documents. The project will result in: 1) improved relevance of search results though identifying finer grained topics in each paragraph in addition to the existing semantic tags; 2) establishing semantic links between the paragraphs in the database so that a researcher can follow topic trails more effectively; and 3) tools for management, analysis, visualization, and summarization of results, user initiated data mining and pattern identification. These will assist researchers identifying and testing hypotheses about the societies they investigate. In addition to working on the eHRAF World Cultures database, the project will provide open access services that any researcher can use to process and analyse their own material.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.