---
_id: '63754'
abstract:
- lang: eng
  text: Data spaces are receiving an emerging interest in Information Systems Research
    and industry practice. They are central to many European research initiatives
    and shape the data economy in Industry 4.0. Generally, they aim to create secure
    environments for cross-organizational data management and sharing. Currently,
    there is considerable interest in developing new data spaces in Industry 4.0,
    also accelerated through regulatory changes. However, key questions about what
    precisely characterizes a data space in Industry 4.0 remain unresolved. Against
    this backdrop, we build a taxonomy of data spaces in the Industry 4.0 context.
    We identified nine distinctive dimensions and 40 corresponding characteristics
    among the 19 data spaces analyzed. The taxonomy enables clearer classification
    and nomenclature of data spaces in this context. This short paper will ignite
    planned further research on data spaces in Industry 4.0 and contribute to a conceptualization
    of a taxonomic theory for interested researchers.
author:
- first_name: Oliver
  full_name: Werth, Oliver
  last_name: Werth
- first_name: Christian
  full_name: Koldewey, Christian
  id: '43136'
  last_name: Koldewey
  orcid: https://orcid.org/0000-0001-7992-6399
- first_name: Mathias
  full_name: Uslar, Mathias
  last_name: Uslar
- first_name: Julian
  full_name: Zerbin, Julian
  id: '51711'
  last_name: Zerbin
citation:
  ama: 'Werth O, Koldewey C, Uslar M, Zerbin J. What Characterizes Data Spaces in
    Industry 4.0? Towards a Better Understanding. In: <i>Lecture Notes in Business
    Information Processing</i>. Springer Nature Switzerland; 2026. doi:<a href="https://doi.org/10.1007/978-3-032-14518-5_3">10.1007/978-3-032-14518-5_3</a>'
  apa: Werth, O., Koldewey, C., Uslar, M., &#38; Zerbin, J. (2026). What Characterizes
    Data Spaces in Industry 4.0? Towards a Better Understanding. <i>Lecture Notes
    in Business Information Processing</i>. 16th International Conference on Software
    Business (ICSOB 2025), Stuttgart, Germany. <a href="https://doi.org/10.1007/978-3-032-14518-5_3">https://doi.org/10.1007/978-3-032-14518-5_3</a>
  bibtex: '@inproceedings{Werth_Koldewey_Uslar_Zerbin_2026, place={Cham}, title={What
    Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding}, DOI={<a
    href="https://doi.org/10.1007/978-3-032-14518-5_3">10.1007/978-3-032-14518-5_3</a>},
    booktitle={Lecture Notes in Business Information Processing}, publisher={Springer
    Nature Switzerland}, author={Werth, Oliver and Koldewey, Christian and Uslar,
    Mathias and Zerbin, Julian}, year={2026} }'
  chicago: 'Werth, Oliver, Christian Koldewey, Mathias Uslar, and Julian Zerbin. “What
    Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding.” In
    <i>Lecture Notes in Business Information Processing</i>. Cham: Springer Nature
    Switzerland, 2026. <a href="https://doi.org/10.1007/978-3-032-14518-5_3">https://doi.org/10.1007/978-3-032-14518-5_3</a>.'
  ieee: 'O. Werth, C. Koldewey, M. Uslar, and J. Zerbin, “What Characterizes Data
    Spaces in Industry 4.0? Towards a Better Understanding,” presented at the 16th
    International Conference on Software Business (ICSOB 2025), Stuttgart, Germany,
    2026, doi: <a href="https://doi.org/10.1007/978-3-032-14518-5_3">10.1007/978-3-032-14518-5_3</a>.'
  mla: Werth, Oliver, et al. “What Characterizes Data Spaces in Industry 4.0? Towards
    a Better Understanding.” <i>Lecture Notes in Business Information Processing</i>,
    Springer Nature Switzerland, 2026, doi:<a href="https://doi.org/10.1007/978-3-032-14518-5_3">10.1007/978-3-032-14518-5_3</a>.
  short: 'O. Werth, C. Koldewey, M. Uslar, J. Zerbin, in: Lecture Notes in Business
    Information Processing, Springer Nature Switzerland, Cham, 2026.'
conference:
  end_date: 2025-11-26
  location: Stuttgart, Germany
  name: 16th International Conference on Software Business (ICSOB 2025)
  start_date: 2025-11-24
date_created: 2026-01-27T11:56:10Z
date_updated: 2026-03-18T07:12:49Z
department:
- _id: '563'
doi: 10.1007/978-3-032-14518-5_3
keyword:
- Industry 4.0
- Taxonomy
- Data spaces
- Characterization
language:
- iso: eng
place: Cham
publication: Lecture Notes in Business Information Processing
publication_identifier:
  isbn:
  - '9783032145178'
  - '9783032145185'
  issn:
  - 1865-1348
  - 1865-1356
publication_status: published
publisher: Springer Nature Switzerland
quality_controlled: '1'
status: public
title: What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding
type: conference
user_id: '51711'
year: '2026'
...
---
_id: '45299'
abstract:
- lang: eng
  text: Many applications are driven by Machine Learning (ML) today. While complex
    ML models lead to an accurate prediction, their inner decision-making is obfuscated.
    However, especially for high-stakes decisions, interpretability and explainability
    of the model are necessary. Therefore, we develop a holistic interpretability
    and explainability framework (HIEF) to objectively describe and evaluate an intelligent
    system’s explainable AI (XAI) capacities. This guides data scientists to create
    more transparent models. To evaluate our framework, we analyse 50 real estate
    appraisal papers to ensure the robustness of HIEF. Additionally, we identify six
    typical types of intelligent systems, so-called archetypes, which range from explanatory
    to predictive, and demonstrate how researchers can use the framework to identify
    blind-spot topics in their domain. Finally, regarding comprehensiveness, we used
    a random sample of six intelligent systems and conducted an applicability check
    to provide external validity.
author:
- first_name: Jan-Peter
  full_name: Kucklick, Jan-Peter
  id: '77066'
  last_name: Kucklick
citation:
  ama: 'Kucklick J-P. HIEF: a holistic interpretability and explainability framework.
    <i>Journal of Decision Systems</i>. Published online 2023:1-41. doi:<a href="https://doi.org/10.1080/12460125.2023.2207268">10.1080/12460125.2023.2207268</a>'
  apa: 'Kucklick, J.-P. (2023). HIEF: a holistic interpretability and explainability
    framework. <i>Journal of Decision Systems</i>, 1–41. <a href="https://doi.org/10.1080/12460125.2023.2207268">https://doi.org/10.1080/12460125.2023.2207268</a>'
  bibtex: '@article{Kucklick_2023, title={HIEF: a holistic interpretability and explainability
    framework}, DOI={<a href="https://doi.org/10.1080/12460125.2023.2207268">10.1080/12460125.2023.2207268</a>},
    journal={Journal of Decision Systems}, publisher={Taylor &#38; Francis}, author={Kucklick,
    Jan-Peter}, year={2023}, pages={1–41} }'
  chicago: 'Kucklick, Jan-Peter. “HIEF: A Holistic Interpretability and Explainability
    Framework.” <i>Journal of Decision Systems</i>, 2023, 1–41. <a href="https://doi.org/10.1080/12460125.2023.2207268">https://doi.org/10.1080/12460125.2023.2207268</a>.'
  ieee: 'J.-P. Kucklick, “HIEF: a holistic interpretability and explainability framework,”
    <i>Journal of Decision Systems</i>, pp. 1–41, 2023, doi: <a href="https://doi.org/10.1080/12460125.2023.2207268">10.1080/12460125.2023.2207268</a>.'
  mla: 'Kucklick, Jan-Peter. “HIEF: A Holistic Interpretability and Explainability
    Framework.” <i>Journal of Decision Systems</i>, Taylor &#38; Francis, 2023, pp.
    1–41, doi:<a href="https://doi.org/10.1080/12460125.2023.2207268">10.1080/12460125.2023.2207268</a>.'
  short: J.-P. Kucklick, Journal of Decision Systems (2023) 1–41.
date_created: 2023-05-26T05:04:45Z
date_updated: 2023-05-26T05:08:36Z
department:
- _id: '195'
- _id: '196'
doi: 10.1080/12460125.2023.2207268
keyword:
- Explainable AI (XAI)
- machine learning
- interpretability
- real estate appraisal
- framework
- taxonomy
language:
- iso: eng
main_file_link:
- url: https://www.tandfonline.com/doi/full/10.1080/12460125.2023.2207268
page: 1-41
publication: Journal of Decision Systems
publication_identifier:
  issn:
  - 1246-0125
  - 2116-7052
publication_status: published
publisher: Taylor & Francis
status: public
title: 'HIEF: a holistic interpretability and explainability framework'
type: journal_article
user_id: '77066'
year: '2023'
...
---
_id: '29539'
abstract:
- lang: eng
  text: Explainable Artificial Intelligence (XAI) is currently an important topic
    for the application of Machine Learning (ML) in high-stakes decision scenarios.
    Related research focuses on evaluating ML algorithms in terms of interpretability.
    However, providing a human understandable explanation of an intelligent system
    does not only relate to the used ML algorithm. The data and features used also
    have a considerable impact on interpretability. In this paper, we develop a taxonomy
    for describing XAI systems based on aspects about the algorithm and data. The
    proposed taxonomy gives researchers and practitioners opportunities to describe
    and evaluate current XAI systems with respect to interpretability and guides the
    future development of this class of systems.
author:
- first_name: Jan-Peter
  full_name: Kucklick, Jan-Peter
  id: '77066'
  last_name: Kucklick
citation:
  ama: 'Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In:
    <i>Wirtschaftsinformatik 2022 Proceedings</i>. ; 2022.'
  apa: Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems.
    <i>Wirtschaftsinformatik 2022 Proceedings</i>. Wirtschaftsinformatik 2022 (WI22),
    Nürnberg (online).
  bibtex: '@inproceedings{Kucklick_2022, title={Towards a model- and data-focused
    taxonomy of XAI systems}, booktitle={Wirtschaftsinformatik 2022 Proceedings},
    author={Kucklick, Jan-Peter}, year={2022} }'
  chicago: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI
    Systems.” In <i>Wirtschaftsinformatik 2022 Proceedings</i>, 2022.
  ieee: J.-P. Kucklick, “Towards a model- and data-focused taxonomy of XAI systems,”
    presented at the Wirtschaftsinformatik 2022 (WI22), Nürnberg (online), 2022.
  mla: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.”
    <i>Wirtschaftsinformatik 2022 Proceedings</i>, 2022.
  short: 'J.-P. Kucklick, in: Wirtschaftsinformatik 2022 Proceedings, 2022.'
conference:
  end_date: 2022-02-23
  location: Nürnberg (online)
  name: Wirtschaftsinformatik 2022 (WI22)
  start_date: 2022-02-21
date_created: 2022-01-26T08:22:03Z
date_updated: 2022-01-26T08:24:30Z
department:
- _id: '195'
- _id: '196'
keyword:
- Explainable Artificial Intelligence
- XAI
- Interpretability
- Decision Support Systems
- Taxonomy
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1056&context=wi2022
oa: '1'
publication: Wirtschaftsinformatik 2022 Proceedings
status: public
title: Towards a model- and data-focused taxonomy of XAI systems
type: conference
user_id: '77066'
year: '2022'
...
---
_id: '5661'
abstract:
- lang: eng
  text: Spam has become one of the most annoying and costly phenomenon in the Internet.
    Valid e-mail addresses belong to the most valuable resources of spammers, but
    little is known about spammers? behavior when collecting and harvesting addresses
    and spammers? capabilities and interest in carefully directed, consumer-oriented
    marketing have not been explored yet. Gaining insight into spammers? ways to obtain
    and (mis)use e-mail addresses is useful in many ways, e.g. for the assessment
    of the effectiveness of address obscuring techniques and the usability and necessity
    of hiding e-mail addresses on the Internet. This paper presents a spam honeypot
    project in progress addressing these issues by systematically placing e-mail addresses
    in the Internet and analyzing received e-mails. The honeypot?s conceptual framework,
    its implementation, and first empirical results are presented. Finally, an outlook
    on further work and activities is provided.
author:
- first_name: Guido
  full_name: Schryen, Guido
  id: '72850'
  last_name: Schryen
citation:
  ama: 'Schryen G. An e-mail honeypot addressing spammers’ behavior in collecting
    and applying addresses. In: <i>Proceedings of the 6th IEEE Information Assurance
    Workshop</i>. Westpoint; 2005:37-41.'
  apa: Schryen, G. (2005). An e-mail honeypot addressing spammers’ behavior in collecting
    and applying addresses. In <i>Proceedings of the 6th IEEE Information Assurance
    Workshop</i> (pp. 37–41). Westpoint.
  bibtex: '@inproceedings{Schryen_2005, title={An e-mail honeypot addressing spammers’
    behavior in collecting and applying addresses}, booktitle={Proceedings of the
    6th IEEE Information Assurance Workshop}, publisher={Westpoint}, author={Schryen,
    Guido}, year={2005}, pages={37–41} }'
  chicago: Schryen, Guido. “An E-Mail Honeypot Addressing Spammers’ Behavior in Collecting
    and Applying Addresses.” In <i>Proceedings of the 6th IEEE Information Assurance
    Workshop</i>, 37–41. Westpoint, 2005.
  ieee: G. Schryen, “An e-mail honeypot addressing spammers’ behavior in collecting
    and applying addresses,” in <i>Proceedings of the 6th IEEE Information Assurance
    Workshop</i>, 2005, pp. 37–41.
  mla: Schryen, Guido. “An E-Mail Honeypot Addressing Spammers’ Behavior in Collecting
    and Applying Addresses.” <i>Proceedings of the 6th IEEE Information Assurance
    Workshop</i>, Westpoint, 2005, pp. 37–41.
  short: 'G. Schryen, in: Proceedings of the 6th IEEE Information Assurance Workshop,
    Westpoint, 2005, pp. 37–41.'
date_created: 2018-11-14T14:55:48Z
date_updated: 2022-01-06T07:02:24Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
  content_type: application/pdf
  creator: hsiemes
  date_created: 2018-12-18T13:31:41Z
  date_updated: 2018-12-18T13:31:41Z
  file_id: '6331'
  file_name: Schryen - An e-mail honeypot addressing spammers' behavior in collecting
    and applying addresses.pdf
  file_size: 119362
  relation: main_file
file_date_updated: 2018-12-18T13:31:41Z
has_accepted_license: '1'
keyword:
- Spam
- ham
- e-mail
- honeypot
- address obscuring technique
- address taxonomy
language:
- iso: eng
oa: '1'
page: 37-41
publication: Proceedings of the 6th IEEE Information Assurance Workshop
publisher: Westpoint
status: public
title: An e-mail honeypot addressing spammers' behavior in collecting and applying
  addresses
type: conference
user_id: '61579'
year: '2005'
...