Michael D. Fischer

Michael D. Fischer is an anthropologist who has worked mainly in the Punjab and Swat in Pakistan, and the Cook Islands, but has field experience on all continents other than Antarctica. His major interests are in the representation and structure of indigenous knowledge, cultural informatics, invention, and the impact of mobile communications on social networks and agency.

Fischer is Vice-President of the Human Relations Area Files (HRAF), Co-Director of HRAF Advanced Research Centers, and PI for HRAF’s NSF-sponsored iKLEWS project to advance eHRAF World Cultures using data science to develop a services platform with services to better leverage HRAF’s resources for a wide range of research where cross-cultural comparison can make a major contribution. He is also Professor of Anthropological Sciences (Emeritus) at the University of Kent.

Email address: M.D.Fischer@kent.ac.uk

Surface Mail:

Human Relations Area Files, 755 Prospect Street, New Haven CT 06511-1225 USA.


Posts and Positions

Selected Publications


I have received grants from the ESRC, AHRB, SERC, MRC, HEFCE, JISC, NSF, Leverhulme and Nuffield, on topics including ethnography of Pakistan and the Cook Islands, formal analysis, multi-media databases, coding methods, virtual reality, performance and large scale networked databases, historical anthropology and textual markup, and ethnographic data mining.

Recent grants include:

Current Grant


iKLEWS (Infrastructure for Knowledge Linkages from Ethnography of World Societies) will create semantic infrastructure and associated computer services for an existing textual database (eHRAF World Cultures), presently with roughly 750000 pages from 6500 ethnographic documents covering 330 world societies over time. The basic goal is to greatly expand the value of eHRAF World Cultures to users who seek to understand the range of possibilities for human understanding, knowledge, belief and behaviour with respect to real-world problems we face today, such as: climate change; violence; disasters; epidemics; hunger; and war. Understanding how and why cultures vary in the range of possible outcomes in similar circumstances is critical to improving policy, applied science, and basic scientific understandings of the human condition. Seeing how others have addressed issues can help us find solutions we might not find otherwise. This is extremely valuable in understanding an increasingly globalized world. It can be used to explore the relationship between human evolution and human behavior. Although the current web version of eHRAF World Cultures is very fast at retrieving relevant ethnography, fundamentally it uses the same method as the original paper files founded in 1949, just a lot faster. There are no aids to analyzing the material once found; the user has to read the results of their search and apply their own methods. This project will begin to fill this gap so that modern methods of working with text can be applied by developing an extensible framework that deploys tools for analysis as well as greatly improving search capability. This will be available as a services framework, that can be used by both beginners and advanced researchers.

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, use of space and time, morality, or music and songs, to use examples that have been investigated using prototypic tools preceding this project, Some of the methods used can be applied in areas as far afield as AI and robotics, such as forming a basis for a bridge between rather opaque deep learning and more transparent logic driven narratives, making AI solutions more human. We are applying pattern extraction and linguistic analysis through deep learning tools to define a flexible logic for the contents of the documents. The project will result in improved relevance of search results though identifying finer grained topics in each paragraph in addition to the OCMs, establishing semantic representations of the paragraphs in the texts with semantic links between the paragraphs so that a researcher can follow topic trails more effectively, and provide 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 HRAF's eHRAF World Cultures database, we will provide services that any researcher can use to process and analyse their own material.

More at the CSAC Centre site.