Understanding Complex Behavior and Decision Making Using Ethnographic Knowledge Elicitation Tools (KnETs)
Bibliographic Data
| ID | 12170989 |
|---|---|
| Authors | Sukaina Bharwani (0000-0002-0152-4565, Stockholm Environment Institute, corresponding author) |
| Year | 2005 |
| Volume | 24 |
| Issue | 1 |
| Pages | 78-105 |
| Publication date | 2005-12-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Science Computer Review (JOURNAL) |
| Journal identifiers | ISSN: 0894-4393 • E-ISSN: 1552-8286 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/0894439305282346 |
| OpenAlex | W1970943423 |
| Language | EN |
| Citations received | 9 |
| References cited | 19 |
Understanding ethnographic data in a formal way is imperative when faced with multiple responses of humans within their environments. Knowledge Elicitation Tools (KnETs) incorporate techniques for modeling knowledge using methods long used in anthropological fieldwork and formalizing knowledge using knowledge engineering methods from computer science. KnETs enhance our understanding of our data to reveal new avenues for enquiry. KnETs support traditional participatory fieldwork methods and produce input for agent-based models, supporting a formalized link between qualitative and quantitative representations of knowledge and their interaction. The fusion of these techniques has resulted in a four-stage process that incorporates consistent verification and validation on data as it is collected by domain experts and informants. The application of this innovative methodology is successful precisely due to the mutual benefits that each technique provides by addressing current bottlenecks in both processes of ethnographic data collection and knowledge engineering
Citizen journalism · Data collection · Data science · Domain (mathematical analysis · Domain knowledge · Ethnography · Knowledge extraction · Knowledge management · Process (computing · Sociology · Computer Science · Data Mining Algorithms and Applications · Language and cultural evolution · Semantic Web and Ontologies · Artificial Intelligence
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| Unique citing works | 9 |
|---|---|
| Citations per year | 0,56 |
| Citation span | 2010 - 2025 (16) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 6 |