---
_id: '34197'
abstract:
- lang: eng
  text: <jats:title>Abstract</jats:title><jats:p>Comprehensive data understanding
    is a key success driver for data analytics projects. Knowing the characteristics
    of the data helps a lot in selecting the appropriate data analysis techniques.
    Especially in data-driven product planning, knowledge about the data is a necessary
    prerequisite because data of the use phase is very heterogeneous. However, companies
    often do not have the necessary know-how or time to build up solid data understanding
    in connection with data analysis. In this paper, we develop a methodology to organize
    and categorize and thus understand use phase data in a way that makes it accessible
    to general data analytics workflows, following a design science research approach.
    We first present a knowledge base that lists typical use phase data from a product
    planning view. Second, we develop a taxonomy based on standard literature and
    real data objects, which covers the diversity of the data considered. The taxonomy
    provides 8 dimensions that support classification of use phase data and allows
    to capture data characteristics from a data analytics view. Finally, we combine
    both views by clustering the objects of the knowledge base according to the taxonomy.
    Each of the resulting clusters covers a typical combination of analytics relevant
    characteristics occurring in practice. By abstracting from the diversity of use
    phase data into artifacts with manageable complexity, our approach provides guidance
    to choose appropriate data analysis and AI techniques.</jats:p>
author:
- first_name: Melina
  full_name: Panzner, Melina
  last_name: Panzner
- first_name: Sebastian
  full_name: von Enzberg, Sebastian
  last_name: von Enzberg
- first_name: Maurice
  full_name: Meyer, Maurice
  last_name: Meyer
- first_name: Roman
  full_name: Dumitrescu, Roman
  last_name: Dumitrescu
citation:
  ama: Panzner M, von Enzberg S, Meyer M, Dumitrescu R. Characterization of Usage
    Data with the Help of Data Classifications. <i>Journal of the Knowledge Economy</i>.
    Published online 2022. doi:<a href="https://doi.org/10.1007/s13132-022-01081-z">10.1007/s13132-022-01081-z</a>
  apa: Panzner, M., von Enzberg, S., Meyer, M., &#38; Dumitrescu, R. (2022). Characterization
    of Usage Data with the Help of Data Classifications. <i>Journal of the Knowledge
    Economy</i>. <a href="https://doi.org/10.1007/s13132-022-01081-z">https://doi.org/10.1007/s13132-022-01081-z</a>
  bibtex: '@article{Panzner_von Enzberg_Meyer_Dumitrescu_2022, title={Characterization
    of Usage Data with the Help of Data Classifications}, DOI={<a href="https://doi.org/10.1007/s13132-022-01081-z">10.1007/s13132-022-01081-z</a>},
    journal={Journal of the Knowledge Economy}, publisher={Springer Science and Business
    Media LLC}, author={Panzner, Melina and von Enzberg, Sebastian and Meyer, Maurice
    and Dumitrescu, Roman}, year={2022} }'
  chicago: Panzner, Melina, Sebastian von Enzberg, Maurice Meyer, and Roman Dumitrescu.
    “Characterization of Usage Data with the Help of Data Classifications.” <i>Journal
    of the Knowledge Economy</i>, 2022. <a href="https://doi.org/10.1007/s13132-022-01081-z">https://doi.org/10.1007/s13132-022-01081-z</a>.
  ieee: 'M. Panzner, S. von Enzberg, M. Meyer, and R. Dumitrescu, “Characterization
    of Usage Data with the Help of Data Classifications,” <i>Journal of the Knowledge
    Economy</i>, 2022, doi: <a href="https://doi.org/10.1007/s13132-022-01081-z">10.1007/s13132-022-01081-z</a>.'
  mla: Panzner, Melina, et al. “Characterization of Usage Data with the Help of Data
    Classifications.” <i>Journal of the Knowledge Economy</i>, Springer Science and
    Business Media LLC, 2022, doi:<a href="https://doi.org/10.1007/s13132-022-01081-z">10.1007/s13132-022-01081-z</a>.
  short: M. Panzner, S. von Enzberg, M. Meyer, R. Dumitrescu, Journal of the Knowledge
    Economy (2022).
date_created: 2022-12-05T12:49:56Z
date_updated: 2022-12-05T12:51:03Z
department:
- _id: '563'
doi: 10.1007/s13132-022-01081-z
keyword:
- Economics and Econometrics
language:
- iso: eng
publication: Journal of the Knowledge Economy
publication_identifier:
  issn:
  - 1868-7865
  - 1868-7873
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Characterization of Usage Data with the Help of Data Classifications
type: journal_article
user_id: '15782'
year: '2022'
...