Hostname: page-component-745bb68f8f-s22k5 Total loading time: 0 Render date: 2025-01-19T00:19:57.923Z Has data issue: false hasContentIssue false
  • English
  • Français

A Database System for Geochemical, Isotope Hydrological, and Geochronological Laboratories

Published online by Cambridge University Press:  18 July 2016

Axel Suckow  and
Ingolf Dumke
Axel Suckow
Affiliation:
Institute for Joint Geoscientific Research (GGA), S3: Geochronology and Isotope Hydrology, Stilleweg 2, Hannover, Germany. Email: [email protected].
Ingolf Dumke
Affiliation:
Federal Institute for Geosciences and Natural Resources (BGR), Stilleweg 2, Hannover, Germany
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We present a data model designed for laboratories in which many different methods are used. The main feature of the model is the recursive relationships of data records in the subsample table. This makes it possible to model all steps from the preparation of the sample to the final value and enables the raw data to be stored together with the final values, even if many preparation steps or many subsamples are involved. We show ways to adopt this basic model to laboratories with many years of data. The data model is extended to include laboratory records and attribute data, e.g. the geographical coordinates of the sampling site or links to the various projects for which the samples are used.

Type
II. Getting More from the Data
Information
Radiocarbon , Volume 43 , Issue 2A: Proceedings of the 17th International Radiocarbon Conference (Part 1 of 3) , 2001 , pp. 325 - 337
Copyright
Copyright © The Arizona Board of Regents on behalf of the University of Arizona 

References

Coplen, TB. 1998. A manual for a laboratory information management system (LIMS) for light stable isotopes. Version 7.0. USGS open file report: 98–284. 124 p.CrossRefGoogle Scholar
DCSD 1995. Guidelines for data documentation. In: Annual report of the Danish Committee on Scientific Dishonesty 1994. Copenhagen: The Danish Research Councils.Google Scholar
DFG 1998 Empfehlungen der DFG-Kommission “Selbstkontrolle in der Wissenschaft”, Vorschläge zur Sicherung guter wissenschaftlicher Praxis. Available at http://www.dfg.de/aktuell/download/empf_selbstkontr.htm.Google Scholar
Geyh, MA. 1972. A comparison: proportional counter and liquid scintillation spectrometer for radiocarbon dating. Proceedings of the VIIIth International Conference on Radiocarbon Dating. Wellington, New Zealand. p 81–93.Google Scholar
Maloszewski, P, Zuber, A. 1982. Determining the turnover time of groundwater systems with the aid of environmental tracers, I. Models and their applicability. Journal of Hydrology 57:207–31.CrossRefGoogle Scholar
Maloszewski, P, Zuber, A. 1996. Lumped parameter models for interpretation of environmental tracer data. Manual on Mathematical Models in Isotope Hydrogeology, IAEA-TECDOC 10:9–58. Vienna.Google Scholar
Suckow, A, Treppke, U, Wiedicke, M, Weber, M. 2001. Bioturbation coefficients of deep-sea sediments from the Peru Basin determined by gamma spectrometry of 210Pbexc . Deep-Sea Research II 48:3569–92.Google Scholar
Suckow, A, Morgenstern, U, Kudrass, HR. 2001. Absolute dating of recent sediments in the cyclone-influenced shelf area off Bangladesh: comparison of gamma spectrometric (137Cs, 210Pb, 228Ra), radiocarbon and 32Si ages. Radiocarbon. This issue.CrossRefGoogle Scholar