Observation-driven geo-ontology engineering
Abstract
Abstract Big Data, Linked Data, Smart Dust, Digital Earth, and e‐Science are just some of the names for research trends that surfaced over the last years. While all of them address different visions and needs, they share a common theme: How do we manage massive amounts of heterogeneous data, derive knowledge out of them instead of drowning in information, and how do we make our findings reproducible and reusable by others? In a network of knowledge, topics span across scientific disciplines and the idea of domain ontologies as common agreements seems like an illusion. In this work, we argue that these trends require a radical paradigm shift in ontology engineering away from a small number of authoritative, global ontologies developed top‐down, to a high number of local ontologies that are driven by application needs and developed bottom‐up out of observation data. Similarly as the early Web was replaced by a social Web in which volunteers produce data instead of purely consuming it, the next generation of knowledge infrastructures has to enable users to become knowledge engineers themselves. Surprisingly, existing ontology engineering frameworks are not well suited for this new perspective. Hence, we propose an observation‐driven ontology engineering framework, show how its layers can be realized using specific methodologies, and relate the framework to existing work on geo‐ontologies.
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ODOE supports both human and technical sensors, and is therefore useful to consider when pairing quantitative and qualitative data.
“ODOE supports both human and technical sensors, and is therefore useful to consider when pairing quantitative (usually coming from technical sensors) and qualitative data (mostly produced by humans).”
From Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience (2016) · cites this paper as [101]
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- Authors
- Janowicz, K.
- Affiliations
- University of California, Santa Barbara (US)
- Corresponding author
- Janowicz, Krzysztof
- ORCID
- Janowicz, Krzysztof
- Venue
- Transactions in GIS
- Publisher
- Wiley
- Published
- 2012-05-28
- Volume
- 16
- Issue
- 3
- Pages
- 351-374
- ISSN
- 1361-1682 (ISSN-L)
- 1467-9671
- OpenAlex
- W1950879617
- Cited by
- 94
- References
- 91
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 7 · 2023: 1 · 2022: 6 · 2021: 3 · 2020: 9 · 2019: 7 · 2018: 6 · 2017: 8 · 2016: 9 · 2015: 11 · 2014: 8 · 2013: 6 · 2012: 5
- FWCI
- 9.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transactions in GIS (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- geo-ontology, local ontologies, observation data, knowledge engineering, heterogeneous data management, knowledge infrastructure, big data, linked data
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