The Isotopic Fingerprint: New Methods of Data Mining and Similarity Search



The generation of an isotopic map of the reference region featuring local stable isotopic fingerprints requires the application of data mining methods due to the heterogeneity and complexity of the generated data. In this chapter, we explore new techniques to process isotopic data with the ultimate goal of constructing a map of locally characteristic isotopic fingerprints that help predict the places of origin of particular findings and, thus, supports archaeologists in deriving and testing hypotheses. In particular, we propose a new method for feature selection and apply it to a sample dataset of animal bones from the reference region. This application confirms that a multivariate fingerprint is clearly superior over univariate analysis and that the impact of oxygen on the reliability of the fingerprints is not very prominent. These findings confirm that it is possible to explore cremated human material for provenance analysis. Based on these results, we also propose a new spatial clustering method for detecting spatially consistent areas of homogeneous isotopic fingerprints resulting in an isotopic map of the reference region.


Isoscapes Isotopic mapping Data mining Feature selection Spatial clustering 


  1. Bowen GJ (2010) Isoscapes: spatial pattern in isotopic biogeochemistry. Annu Rev Earth Planet Sci 38:161–187CrossRefGoogle Scholar
  2. Bumsted M (1981) The potential of stable carbon isotopes in bioarchaeological anthropology. Biocultural adaptation—comprehensive approaches to skeletal analyses, pp 108–127Google Scholar
  3. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B Methodolol 39:1–38Google Scholar
  4. DeNiro M (1985) Postmortem preservation and alteration of in vivo bone collagen isotope ratios in relation to palaeodietary reconstruction. Nature 317:806–809CrossRefGoogle Scholar
  5. Ericson J (1985) Strontium isotope characterization in the study of prehistoric human ecology. J Hum Evol 14:503–514CrossRefGoogle Scholar
  6. Grupe G, Price TD, Schröter P, Söllner F, Johnson CM, Beard BL (1997) Mobility of Bell Beaker people revealed by strontium isotope ratios of tooth and bone: a study of southern Bavarian skeletal remains. Appl Geochem 12:517–525CrossRefGoogle Scholar
  7. Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182Google Scholar
  8. Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2015) EM. Accessed 10 Mar 2015
  9. Hubert L, Arabie P (1985) Comparing partitions. J Classif 2(1):193–218CrossRefGoogle Scholar
  10. Kern Z, Kohán B, Leuenberger M (2014) Precipitation isoscape of high reliefs: interpolation scheme designed and tested for monthly resolved precipitation oxygen isotope records of an Alpine domain. Atmos Chem Phys 14:1897–1907CrossRefGoogle Scholar
  11. Milligan GW, Cooper MC (1987) Methodology review: clustering methods. Appl Psychol Meas 11(4):329–354CrossRefGoogle Scholar
  12. Molleson TI, Eldridge D, Gale N (1986) Identification of lead sources by stable isotope ratios in bones and lead from Poundbury Camp, Dorset. Oxf J Archaeol 5:249–253CrossRefGoogle Scholar
  13. Norr L (1984) Prehistoric subsistence and health status of coastal peoples from the Panamanian Isthmus of lower Central America. Paleopathology at the origins of agriculture, pp 463–480Google Scholar
  14. Rand WM (1971) Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66(336):846–850CrossRefGoogle Scholar
  15. Schoeninger MJ, DeNiro M, Tauber H (1983) Stable nitrogen isotope ratios of bone collagen reflects marine and terrestrial components of prehistoric human diet. Science 220:1380–1383CrossRefGoogle Scholar
  16. Schwarz HP, Melbye J, Katzenberg MA, Knyf M (1985) Stable isotopes in human skeletons of southern Ontario: reconstructing paleodiet. J Archaeol Sci 12:187–206CrossRefGoogle Scholar
  17. Vinh NX, Epps J, Bailey J (2010) Information theoretic measures for clusterings comparison: variants, properties, normalization and correction for chance. J Mach Learn Res 11:2837–2854Google Scholar
  18. Vogel J, van der Merwe N (1977) Isotopic evidence for early maize cultivation in New York state. Am Antiq 42:238–242CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute for InformaticsLudwig-Maximilians-Universität MünchenMunichGermany
  2. 2.Faculty of Electrical Engineering and Computer ScienceLeibniz Universität HannoverHannoverGermany

Personalised recommendations