@article{8764195,
  abstract     = {{The availability and use of new and emerging data sources has increased exponentially. The variety of these data sources offers opportunities to complement, replace, improve or add to conventional data sources. Survey data is one kind of these conventional data sources. In survey research, a framework to assess the accuracy of survey data already has been around for quite some time, and goes by the name of the Total Survey Error (TSE) framework. The philosophy behind this framework has only recently been universalized to (big) data in general in the form of the Total Error Framework (TEF). The current study introduces the TEF to the methodological toolkit of scholars and practitioners in criminology and criminal justice by outlining this generic framework and applying it to an empirical case study (on calculating spatially-referenced crime rates) utilizing two types of administrative data and mobile phone data. The present study discusses the added value and limitations of adapting the TEF, providing guidance to apply the TEF in research and practice. Finally, we propose promising avenues for future inquiries.}},
  author       = {{Snaphaan, Thom and Hardyns, Wim and Pauwels, Lieven}},
  issn         = {{0735-648X}},
  journal      = {{JOURNAL OF CRIME & JUSTICE}},
  keywords     = {{Accuracy,big data,criminal justice,criminology,data quality,Total Error Framework,BIG DATA,SOCIAL DISORGANIZATION,ADMINISTRATIVE DATA,CRIME,QUALITY,IMPACT,CALLS,CITY,TSE}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{112--129}},
  title        = {{Expanding the methodological toolkit of criminology and criminal justice with the Total Error Framework}},
  url          = {{http://doi.org/10.1080/0735648X.2022.2114099}},
  volume       = {{47}},
  year         = {{2024}},
}

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