East European Conference on Advances in Databases and Information Systems

ADBIS 2015: Advances in Databases and Information Systems pp 261-274

ForCE: Is Estimation of Data Completeness Through Time Series Forecasts Feasible?

  • Gregor Endler
  • Philipp Baumgärtel
  • Andreas M. Wahl
  • Richard Lenz
Conference paper

DOI: 10.1007/978-3-319-23135-8_18

Volume 9282 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Endler G., Baumgärtel P., Wahl A.M., Lenz R. (2015) ForCE: Is Estimation of Data Completeness Through Time Series Forecasts Feasible?. In: Tadeusz M., Valduriez P., Bellatreche L. (eds) Advances in Databases and Information Systems. ADBIS 2015. Lecture Notes in Computer Science, vol 9282. Springer, Cham

Abstract

Measuring the completeness of a data population often requires either expert knowledge or the presence of reference data. If neither is available, measuring population completeness becomes nontrivial. We present the ForCE approach (Forecasting for Completeness Estimation), a method to estimate the completeness of timestamped data using time series forecasting. We evaluate the method’s feasibility using a medical domain real-world dataset, which we provide for download. The method is compared to three baselines. ForCE manages to surpass all three.

Keywords

Data quality Population completeness Time series Forecasting 

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gregor Endler
    • 1
  • Philipp Baumgärtel
    • 1
  • Andreas M. Wahl
    • 1
  • Richard Lenz
    • 1
  1. 1.Computer Science 6 (Data Management)Friedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany