An ontology driven relational geochemical database for the earth's critical zone: CZchemDB

X. Z. Niu, J. Z. Williams, D. Miller, K. Lehnert, B. Bills, S. L. Brantley

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Multiple Critical Zone Observatories (CZO) have been established in recent years in the U.S.A. and elsewhere to conduct collaborative, multidisciplinary research on the earth's critical zone (CZ). As a result, a large amount of scientific data over space and time has been collected. However, heterogeneities in data documentation impede our ability for cross-site comparisons and for integrated analysis. To promote efficient data sharing, publishing, and integration, we developed a sample-based measurement ontology (SMO) to formalize data structures and unify variable terms in data documentations for the CZOs. "Sample" is the core of the SMO. Each sample is part of a "Medium" that represents an entity of the CZ such as soils. Characteristics of a sample are analyzed and the results are reported as values and errors. Based on the concepts of the SMO and geochemical data model of Lehnert et al. (2000), we created a relational database to accommodate CZ regolith geochemical data, namely CZchemDB, to bridge the gap between data collection, documentation and sharing among the CZOs. The CZchemDB has now been successfully implemented in the MS Access database management system for individual or small group uses. However, our ultimate goal is to integrate the CZchemDB with the online global geochemistry data portal, EarthChem, for broader data accessibility and reusability. Finally, we emphasize that the SMO is extensible to all media within the CZ and so CZchemDB can be used to store any sample-based chemical data measured on any medium such as minerals, water, gas, or biota in the CZ.

Original languageEnglish (US)
Pages (from-to)10-23
Number of pages14
JournalJournal of Environmental Informatics
Issue number2
StatePublished - Jun 2014

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Environmental Science(all)
  • Computer Science Applications


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