---
_id: '48878'
abstract:
- lang: eng
text: Due to the rise of continuous data-generating applications, analyzing data
streams has gained increasing attention over the past decades. A core research
area in stream data is stream classification, which categorizes or detects data
points within an evolving stream of observations. Areas of stream classification
are diverse\textemdash ranging, e.g., from monitoring sensor data to analyzing
a wide range of (social) media applications. Research in stream classification
is related to developing methods that adapt to the changing and potentially volatile
data stream. It focuses on individual aspects of the stream classification pipeline,
e.g., designing suitable algorithm architectures, an efficient train and test
procedure, or detecting so-called concept drifts. As a result of the many different
research questions and strands, the field is challenging to grasp, especially
for beginners. This survey explores, summarizes, and categorizes work within the
domain of stream classification and identifies core research threads over the
past few years. It is structured based on the stream classification process to
facilitate coordination within this complex topic, including common application
scenarios and benchmarking data sets. Thus, both newcomers to the field and experts
who want to widen their scope can gain (additional) insight into this research
area and find starting points and pointers to more in-depth literature on specific
issues and research directions in the field.
author:
- first_name: Lena
full_name: Clever, Lena
last_name: Clever
- first_name: Janina Susanne
full_name: Pohl, Janina Susanne
last_name: Pohl
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Clever L, Pohl JS, Bossek J, Kerschke P, Trautmann H. Process-Oriented Stream
Classification Pipeline: A Literature Review. Applied Sciences. 2022;12(18):9094.
doi:10.3390/app12189094'
apa: 'Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022).
Process-Oriented Stream Classification Pipeline: A Literature Review. Applied
Sciences, 12(18), 9094. https://doi.org/10.3390/app12189094'
bibtex: '@article{Clever_Pohl_Bossek_Kerschke_Trautmann_2022, title={Process-Oriented
Stream Classification Pipeline: A Literature Review}, volume={12}, DOI={10.3390/app12189094},
number={18}, journal={Applied Sciences}, publisher={{Multidisciplinary Digital
Publishing Institute}}, author={Clever, Lena and Pohl, Janina Susanne and Bossek,
Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2022}, pages={9094} }'
chicago: 'Clever, Lena, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, and
Heike Trautmann. “Process-Oriented Stream Classification Pipeline: A Literature
Review.” Applied Sciences 12, no. 18 (2022): 9094. https://doi.org/10.3390/app12189094.'
ieee: 'L. Clever, J. S. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Process-Oriented
Stream Classification Pipeline: A Literature Review,” Applied Sciences,
vol. 12, no. 18, p. 9094, 2022, doi: 10.3390/app12189094.'
mla: 'Clever, Lena, et al. “Process-Oriented Stream Classification Pipeline: A Literature
Review.” Applied Sciences, vol. 12, no. 18, {Multidisciplinary Digital
Publishing Institute}, 2022, p. 9094, doi:10.3390/app12189094.'
short: L. Clever, J.S. Pohl, J. Bossek, P. Kerschke, H. Trautmann, Applied Sciences
12 (2022) 9094.
date_created: 2023-11-14T15:58:57Z
date_updated: 2023-12-13T10:50:56Z
department:
- _id: '819'
doi: 10.3390/app12189094
intvolume: ' 12'
issue: '18'
keyword:
- big data
- data mining
- data stream analysis
- machine learning
- stream classification
- supervised learning
language:
- iso: eng
page: '9094'
publication: Applied Sciences
publication_identifier:
issn:
- 2076-3417
publisher: '{Multidisciplinary Digital Publishing Institute}'
status: public
title: 'Process-Oriented Stream Classification Pipeline: A Literature Review'
type: journal_article
user_id: '102979'
volume: 12
year: '2022'
...
---
_id: '17156'
abstract:
- lang: eng
text: Business Process Management is a boundary-spanning discipline that aligns
operational capabilities and technology to design and manage business processes.
The Digital Transformation has enabled human actors, information systems, and
smart products to interact with each other via multiple digital channels. The
emergence of this hyper-connected world greatly leverages the prospects of business
processes – but also boosts their complexity to a new level. We need to discuss
how the BPM discipline can find new ways for identifying, analyzing, designing,
implementing, executing, and monitoring business processes. In this research note,
selected transformative trends are explored and their impact on current theories
and IT artifacts in the BPM discipline is discussed to stimulate transformative
thinking and prospective research in this field.
article_type: original
author:
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Joos C. A. M.
full_name: Buijs, Joos C. A. M.
last_name: Buijs
- first_name: Jörg
full_name: Becker, Jörg
last_name: Becker
- first_name: Claudio
full_name: Di Ciccio, Claudio
last_name: Di Ciccio
- first_name: Wil M. P.
full_name: van der Aalst, Wil M. P.
last_name: van der Aalst
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
- first_name: Marco
full_name: Comuzzi, Marco
last_name: Comuzzi
- first_name: Karsten
full_name: Kraume, Karsten
last_name: Kraume
- first_name: Henrik
full_name: Leopold, Henrik
last_name: Leopold
- first_name: Martin
full_name: Matzner, Martin
last_name: Matzner
- first_name: Jan
full_name: Mendling, Jan
last_name: Mendling
- first_name: Nadine
full_name: Ogonek, Nadine
last_name: Ogonek
- first_name: Till
full_name: Post, Till
last_name: Post
- first_name: Manuel
full_name: Resinas, Manuel
last_name: Resinas
- first_name: Kate
full_name: Revoredo, Kate
last_name: Revoredo
- first_name: Adela
full_name: del-Río-Ortega, Adela
last_name: del-Río-Ortega
- first_name: Marcello
full_name: La Rosa, Marcello
last_name: La Rosa
- first_name: Flávia Maria
full_name: Santoro, Flávia Maria
last_name: Santoro
- first_name: Andreas
full_name: Solti, Andreas
last_name: Solti
- first_name: Minseok
full_name: Song, Minseok
last_name: Song
- first_name: Armin
full_name: Stein, Armin
last_name: Stein
- first_name: Matthias
full_name: Stierle, Matthias
last_name: Stierle
- first_name: Verena
full_name: Wolf, Verena
id: '23633'
last_name: Wolf
citation:
ama: Beverungen D, Buijs JCAM, Becker J, et al. Seven Paradoxes of Business Process
Management in a Hyper-Connected World. Business & Information Systems Engineering.
2020;63:145-156. doi:10.1007/s12599-020-00646-z
apa: Beverungen, D., Buijs, J. C. A. M., Becker, J., Di Ciccio, C., van der Aalst,
W. M. P., Bartelheimer, C., vom Brocke, J., Comuzzi, M., Kraume, K., Leopold,
H., Matzner, M., Mendling, J., Ogonek, N., Post, T., Resinas, M., Revoredo, K.,
del-Río-Ortega, A., La Rosa, M., Santoro, F. M., … Wolf, V. (2020). Seven Paradoxes
of Business Process Management in a Hyper-Connected World. Business & Information
Systems Engineering, 63, 145–156. https://doi.org/10.1007/s12599-020-00646-z
bibtex: '@article{Beverungen_Buijs_Becker_Di Ciccio_van der Aalst_Bartelheimer_vom
Brocke_Comuzzi_Kraume_Leopold_et al._2020, title={Seven Paradoxes of Business
Process Management in a Hyper-Connected World}, volume={63}, DOI={10.1007/s12599-020-00646-z},
journal={Business & Information Systems Engineering}, publisher={SpringerNature},
author={Beverungen, Daniel and Buijs, Joos C. A. M. and Becker, Jörg and Di Ciccio,
Claudio and van der Aalst, Wil M. P. and Bartelheimer, Christian and vom Brocke,
Jan and Comuzzi, Marco and Kraume, Karsten and Leopold, Henrik and et al.}, year={2020},
pages={145–156} }'
chicago: 'Beverungen, Daniel, Joos C. A. M. Buijs, Jörg Becker, Claudio Di Ciccio,
Wil M. P. van der Aalst, Christian Bartelheimer, Jan vom Brocke, et al. “Seven
Paradoxes of Business Process Management in a Hyper-Connected World.” Business
& Information Systems Engineering 63 (2020): 145–56. https://doi.org/10.1007/s12599-020-00646-z.'
ieee: 'D. Beverungen et al., “Seven Paradoxes of Business Process Management
in a Hyper-Connected World,” Business & Information Systems Engineering,
vol. 63, pp. 145–156, 2020, doi: 10.1007/s12599-020-00646-z.'
mla: Beverungen, Daniel, et al. “Seven Paradoxes of Business Process Management
in a Hyper-Connected World.” Business & Information Systems Engineering,
vol. 63, SpringerNature, 2020, pp. 145–56, doi:10.1007/s12599-020-00646-z.
short: D. Beverungen, J.C.A.M. Buijs, J. Becker, C. Di Ciccio, W.M.P. van der Aalst,
C. Bartelheimer, J. vom Brocke, M. Comuzzi, K. Kraume, H. Leopold, M. Matzner,
J. Mendling, N. Ogonek, T. Post, M. Resinas, K. Revoredo, A. del-Río-Ortega, M.
La Rosa, F.M. Santoro, A. Solti, M. Song, A. Stein, M. Stierle, V. Wolf, Business
& Information Systems Engineering 63 (2020) 145–156.
date_created: 2020-06-24T10:40:45Z
date_updated: 2024-04-18T12:50:57Z
ddc:
- '380'
department:
- _id: '526'
doi: 10.1007/s12599-020-00646-z
file:
- access_level: closed
content_type: application/pdf
creator: dabe
date_created: 2024-04-18T12:49:25Z
date_updated: 2024-04-18T12:49:25Z
file_id: '53574'
file_name: Business_Process_Management_in_a_Hyperconnected_World.pdf
file_size: 360869
relation: main_file
success: 1
file_date_updated: 2024-04-18T12:49:25Z
has_accepted_license: '1'
intvolume: ' 63'
keyword:
- Business process management (BPM)
- Social computing
- Smart devices
- Big data analytics
- Real-time computing
- BPM life-cycle
language:
- iso: eng
page: 145-156
project:
- _id: '1070'
call_identifier: MSCA-RISE-2014
grant_number: '645751'
name: 'RISE_BPM: Propelling Business Process Management by Research and Innovation
Staff Exchange'
publication: Business & Information Systems Engineering
publication_identifier:
issn:
- 2363-7005
- 1867-0202
publication_status: published
publisher: SpringerNature
quality_controlled: '1'
status: public
title: Seven Paradoxes of Business Process Management in a Hyper-Connected World
type: journal_article
user_id: '59677'
volume: 63
year: '2020'
...
---
_id: '5910'
author:
- first_name: Birte
full_name: Heinemann, Birte
last_name: Heinemann
- first_name: Simone
full_name: Opel, Simone
last_name: Opel
- first_name: Lea
full_name: Budde, Lea
last_name: Budde
- first_name: Carsten
full_name: Schulte, Carsten
last_name: Schulte
- first_name: Daniel
full_name: Frischemeier, Daniel
last_name: Frischemeier
- first_name: Rolf
full_name: Biehler, Rolf
last_name: Biehler
- first_name: Susanne
full_name: Podworny, Susanne
last_name: Podworny
- first_name: Thomas
full_name: Wassong, Thomas
id: '21241'
last_name: Wassong
citation:
ama: Heinemann B, Opel S, Budde L, et al. Drafting a Data Science Curriculum for
Secondary Schools. Proceedings of the 18th Koli Calling International Conference
on Computing Education Research - Koli Calling ’18. 2018;(17):1-5. doi:10.1145/3279720.3279737
apa: Heinemann, B., Opel, S., Budde, L., Schulte, C., Frischemeier, D., Biehler,
R., … Wassong, T. (2018). Drafting a Data Science Curriculum for Secondary Schools.
Proceedings of the 18th Koli Calling International Conference on Computing
Education Research - Koli Calling ’18, (17), 1–5. https://doi.org/10.1145/3279720.3279737
bibtex: '@article{Heinemann_Opel_Budde_Schulte_Frischemeier_Biehler_Podworny_Wassong_2018,
title={Drafting a Data Science Curriculum for Secondary Schools}, DOI={10.1145/3279720.3279737},
number={17}, journal={Proceedings of the 18th Koli Calling International Conference
on Computing Education Research - Koli Calling ’18}, author={Heinemann, Birte
and Opel, Simone and Budde, Lea and Schulte, Carsten and Frischemeier, Daniel
and Biehler, Rolf and Podworny, Susanne and Wassong, Thomas}, year={2018}, pages={1–5}
}'
chicago: 'Heinemann, Birte, Simone Opel, Lea Budde, Carsten Schulte, Daniel Frischemeier,
Rolf Biehler, Susanne Podworny, and Thomas Wassong. “Drafting a Data Science Curriculum
for Secondary Schools.” Proceedings of the 18th Koli Calling International
Conference on Computing Education Research - Koli Calling ’18, no. 17 (2018):
1–5. https://doi.org/10.1145/3279720.3279737.'
ieee: B. Heinemann et al., “Drafting a Data Science Curriculum for Secondary
Schools,” Proceedings of the 18th Koli Calling International Conference on
Computing Education Research - Koli Calling ’18, no. 17, pp. 1–5, 2018.
mla: Heinemann, Birte, et al. “Drafting a Data Science Curriculum for Secondary
Schools.” Proceedings of the 18th Koli Calling International Conference on
Computing Education Research - Koli Calling ’18, no. 17, 2018, pp. 1–5, doi:10.1145/3279720.3279737.
short: B. Heinemann, S. Opel, L. Budde, C. Schulte, D. Frischemeier, R. Biehler,
S. Podworny, T. Wassong, Proceedings of the 18th Koli Calling International Conference
on Computing Education Research - Koli Calling ’18 (2018) 1–5.
date_created: 2018-11-27T10:44:10Z
date_updated: 2022-01-06T07:02:47Z
doi: 10.1145/3279720.3279737
issue: '17'
keyword:
- Curriculum Development
- Data Science
- Secondary Sc
- acm reference format
- big data
- curriculum development
- data literacy
- data science
- educa-
- interdisciplinary
- secondary schools
- tion
language:
- iso: eng
page: 1-5
publication: Proceedings of the 18th Koli Calling International Conference on Computing
Education Research - Koli Calling '18
publication_identifier:
isbn:
- '9781450365352'
publication_status: published
status: public
title: Drafting a Data Science Curriculum for Secondary Schools
type: journal_article
user_id: '21241'
year: '2018'
...
---
_id: '4689'
author:
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Iris
full_name: Junglas, Iris
last_name: Junglas
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
- first_name: Stefan
full_name: Debortoli, Stefan
last_name: Debortoli
citation:
ama: 'Müller O, Junglas I, vom Brocke J, Debortoli S. Utilizing big data analytics
for information systems research: Challenges, promises and guidelines. European
Journal of Information Systems. 2016;(4):289--302. doi:10.1057/ejis.2016.2'
apa: 'Müller, O., Junglas, I., vom Brocke, J., & Debortoli, S. (2016). Utilizing
big data analytics for information systems research: Challenges, promises and
guidelines. European Journal of Information Systems, (4), 289--302. https://doi.org/10.1057/ejis.2016.2'
bibtex: '@article{Müller_Junglas_vom Brocke_Debortoli_2016, title={Utilizing big
data analytics for information systems research: Challenges, promises and guidelines},
DOI={10.1057/ejis.2016.2}, number={4},
journal={European Journal of Information Systems}, author={Müller, Oliver and
Junglas, Iris and vom Brocke, Jan and Debortoli, Stefan}, year={2016}, pages={289--302}
}'
chicago: 'Müller, Oliver, Iris Junglas, Jan vom Brocke, and Stefan Debortoli. “Utilizing
Big Data Analytics for Information Systems Research: Challenges, Promises and
Guidelines.” European Journal of Information Systems, no. 4 (2016): 289--302.
https://doi.org/10.1057/ejis.2016.2.'
ieee: 'O. Müller, I. Junglas, J. vom Brocke, and S. Debortoli, “Utilizing big data
analytics for information systems research: Challenges, promises and guidelines,”
European Journal of Information Systems, no. 4, pp. 289--302, 2016.'
mla: 'Müller, Oliver, et al. “Utilizing Big Data Analytics for Information Systems
Research: Challenges, Promises and Guidelines.” European Journal of Information
Systems, no. 4, 2016, pp. 289--302, doi:10.1057/ejis.2016.2.'
short: O. Müller, I. Junglas, J. vom Brocke, S. Debortoli, European Journal of Information
Systems (2016) 289--302.
date_created: 2018-10-12T08:29:46Z
date_updated: 2022-01-06T07:01:18Z
doi: 10.1057/ejis.2016.2
extern: '1'
issue: '4'
keyword:
- analytics
- big data
- data source
- information systems research
- methodology
language:
- iso: eng
page: 289--302
publication: European Journal of Information Systems
publication_identifier:
isbn:
- 0960-085X
issn:
- '14769344'
status: public
title: 'Utilizing big data analytics for information systems research: Challenges,
promises and guidelines'
type: journal_article
user_id: '72849'
year: '2016'
...
---
_id: '4695'
author:
- first_name: Stefan
full_name: Debortoli, Stefan
last_name: Debortoli
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
citation:
ama: 'Debortoli S, Müller O, vom Brocke J. Comparing business intelligence and big
data skills: A text mining study using job advertisements. Business and Information
Systems Engineering. 2014;(5):289--300. doi:10.1007/s12599-014-0344-2'
apa: 'Debortoli, S., Müller, O., & vom Brocke, J. (2014). Comparing business
intelligence and big data skills: A text mining study using job advertisements.
Business and Information Systems Engineering, (5), 289--300. https://doi.org/10.1007/s12599-014-0344-2'
bibtex: '@article{Debortoli_Müller_vom Brocke_2014, title={Comparing business intelligence
and big data skills: A text mining study using job advertisements}, DOI={10.1007/s12599-014-0344-2},
number={5}, journal={Business and Information Systems Engineering}, author={Debortoli,
Stefan and Müller, Oliver and vom Brocke, Jan}, year={2014}, pages={289--300}
}'
chicago: 'Debortoli, Stefan, Oliver Müller, and Jan vom Brocke. “Comparing Business
Intelligence and Big Data Skills: A Text Mining Study Using Job Advertisements.”
Business and Information Systems Engineering, no. 5 (2014): 289--300. https://doi.org/10.1007/s12599-014-0344-2.'
ieee: 'S. Debortoli, O. Müller, and J. vom Brocke, “Comparing business intelligence
and big data skills: A text mining study using job advertisements,” Business
and Information Systems Engineering, no. 5, pp. 289--300, 2014.'
mla: 'Debortoli, Stefan, et al. “Comparing Business Intelligence and Big Data Skills:
A Text Mining Study Using Job Advertisements.” Business and Information Systems
Engineering, no. 5, 2014, pp. 289--300, doi:10.1007/s12599-014-0344-2.'
short: S. Debortoli, O. Müller, J. vom Brocke, Business and Information Systems
Engineering (2014) 289--300.
date_created: 2018-10-12T08:30:31Z
date_updated: 2022-01-06T07:01:18Z
doi: 10.1007/s12599-014-0344-2
extern: '1'
issue: '5'
keyword:
- Big data
- Business intelligence
- Competencies
- Latent semantic analysis
- Text mining
language:
- iso: eng
page: 289--300
publication: Business and Information Systems Engineering
publication_identifier:
isbn:
- 0910-8327 (Print)$\backslash$n0910-8327 (Linking)
issn:
- '18670202'
status: public
title: 'Comparing business intelligence and big data skills: A text mining study using
job advertisements'
type: journal_article
user_id: '72849'
year: '2014'
...
---
_id: '4696'
author:
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
- first_name: Stefan
full_name: Debortoli, Stefan
last_name: Debortoli
- first_name: Nadine
full_name: Reuter, Nadine
last_name: Reuter
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'vom Brocke J, Debortoli S, Reuter N, Müller O. How In-Memory Technology Can
Create Business Value: Lessons Learned from Hilti. Communications of the Association
for Information Systems. 2014:151--167. doi:10.17705/1CAIS.03407'
apa: 'vom Brocke, J., Debortoli, S., Reuter, N., & Müller, O. (2014). How In-Memory
Technology Can Create Business Value: Lessons Learned from Hilti. Communications
of the Association for Information Systems, 151--167. https://doi.org/10.17705/1CAIS.03407'
bibtex: '@article{vom Brocke_Debortoli_Reuter_Müller_2014, title={How In-Memory
Technology Can Create Business Value: Lessons Learned from Hilti}, DOI={10.17705/1CAIS.03407},
journal={Communications of the Association for Information Systems}, author={vom
Brocke, Jan and Debortoli, Stefan and Reuter, Nadine and Müller, Oliver}, year={2014},
pages={151--167} }'
chicago: 'Brocke, Jan vom, Stefan Debortoli, Nadine Reuter, and Oliver Müller. “How
In-Memory Technology Can Create Business Value: Lessons Learned from Hilti.” Communications
of the Association for Information Systems, 2014, 151--167. https://doi.org/10.17705/1CAIS.03407.'
ieee: 'J. vom Brocke, S. Debortoli, N. Reuter, and O. Müller, “How In-Memory Technology
Can Create Business Value: Lessons Learned from Hilti,” Communications of the
Association for Information Systems, pp. 151--167, 2014.'
mla: 'vom Brocke, Jan, et al. “How In-Memory Technology Can Create Business Value:
Lessons Learned from Hilti.” Communications of the Association for Information
Systems, 2014, pp. 151--167, doi:10.17705/1CAIS.03407.'
short: J. vom Brocke, S. Debortoli, N. Reuter, O. Müller, Communications of the
Association for Information Systems (2014) 151--167.
date_created: 2018-10-12T08:30:38Z
date_updated: 2022-01-06T07:01:18Z
doi: 10.17705/1CAIS.03407
extern: '1'
keyword:
- Advanced business analytics
- Big Data
- Business intelligence
- IT business value
- In-memory technology
- OLAP
- OLTP
- Realtime analytics
- Sentiment analysis
language:
- iso: eng
page: 151--167
publication: Communications of the Association for Information Systems
publication_identifier:
issn:
- '15293181'
status: public
title: 'How In-Memory Technology Can Create Business Value: Lessons Learned from Hilti'
type: journal_article
user_id: '72849'
year: '2014'
...