Earth observation technologies have developed rapidly during the past few decades. Substantial amounts of earth observation data have been acquired and are currently stored in the literature and databases for various research fields such as climatology, oceanography, agriculture, and ecology. Analyzing and integrating such data might produce valuable data products to promote better understanding of the global environment and to help solve global environmental issues. However, most institutions store and manage their earth observation data independently, with little metadata. Scientists have to struggle to search for valuable data from information outside their research domains and seek uses for these. This paper introduces a conceptual model of earth observation data. Utilizing a model to express earth observation items associated with ontologies, the model is a simple quintuple with information extracted from conventional data models, and it is used to uniquely determine portions of earth observation data, which enables flexible annotations to these data. We also introduce our systems to manage the metadata and user interfaces to encourage users to add annotations to earth observation data that can help scientists discover and understand useful information that can support their research.
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Artificial Intelligence