Advances in semantic technology mean that it is now possible to represent ecological data consistently within a framework that is flexible, can be extended over time, and records all of the available knowledge associated with that data.
A ‘semantic model’ allows the content, meaning and context of ecological data to be represented and stored in a rich and consistent format. This aids scientists and others to understand and re-use the data. This is achieved by applying ontologies expressing a formal definition of all the concepts present in the available ecological datasets and the relationships amongst those concepts. This approach records the field observations consistently, provides structured descriptions to express the data’s meaning and context, and applies controlled vocabularies to give consistent labelling and values for semantic searching.
A framework of this kind makes it easier to find information because it is uniformly structured and described – once you learn how to read one dataset, you know how to read all datasets within ÆKOS.
Although this approach is highly innovative, there are many precedents from other branches of science. In particular, genomics has been applying this approach for some time. Eco-informatics Facility experts have also taken inspiration from international initiatives that are embracing the semantic technologies that have emerged over the past decade.
These include the Global Biodiversity Information Facility, SOnet (Sematic Observation Network and SEMtools), DataONE, KNB tool (the Knowledge Network for Biocomplexity), SERONTO (within the LTER Europe/ALTER-Net project), the EuroGEOSS Project (European Commissin initiative of GEOSS – the Global Earth Observation System of Systems), and the National Biocomplexity Information Infrastructure, all of which have embraced the semantic technologies which have emerged over the past decade.
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