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The eReefs data brokering layer for hydrological and environmental data
Author(s) -
Jonathan Yu,
Benjamin Leighton,
Nicholas Car,
S Seaton,
Jonathan Hodge
Publication year - 2015
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2015.165
Subject(s) - metadata , computer science , data element , data discovery , context (archaeology) , ontology , data science , data access , metadata repository , data integration , environmental data , information retrieval , data mining , database , world wide web , paleontology , philosophy , epistemology , biology , political science , law
The environmental sciences are witnessing a data revolution as large amounts of data are being made available at an increasing rate. Many datasets are being published through operational monitoring programs, research activities and global earth observation virtual laboratories. An important aspect is the ability to query relevant metadata which can potentially provide useful information to discover, access and interpret environmental datasets, information about the data providers themselves, data services, data encodings, observation and measurement properties and data service endpoints. However, support for producing and accessing metadata descriptions in a flexible, extensible, easily integrated and easily discovered manner is lacking as current methods require interpreting multiple standards and formalisms. In this paper, we propose components to streamline discovery and access of hydrological and environmental data: a Data Provider Node ontology (DPN-O) which allows precise descriptions to be captured about datasets, data services and their interfaces; and a Data Brokering Layer which provides an API for registering metadata for discovery and query of registered DPN datasets. We discuss this work in the context of the eReefs project which is developing an integrated information platform for discovery and visualization of observational and modelled data of the Great Barrier Reef.

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