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A systematic literature review of machine learning canvases

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

A systematic literature review of machine learning canvases. / Thiée, Lukas-Walter.
INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin: Computer Science and Sustainability. ed. / Gesellschaft für Informatik e.V. (GI). Bonn: Gesellschaft für Informatik e.V., 2021. p. 1221-1235 (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings ; Vol. P-314).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Thiée, L-W 2021, A systematic literature review of machine learning canvases. in Gesellschaft für Informatik e.V. (GI) (ed.), INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin: Computer Science and Sustainability. GI-Edition: Lecture Notes in Informatics (LNI), Proceedings , vol. P-314, Gesellschaft für Informatik e.V., Bonn, pp. 1221-1235, 51. Jahrestagung der Gesellschaft für Informatik - INFORMATIK 2021, Berlin, Berlin, Germany, 27.09.21. https://doi.org/10.18420/informatik2021-101

APA

Thiée, L.-W. (2021). A systematic literature review of machine learning canvases. In Gesellschaft für Informatik e.V. (GI) (Ed.), INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin: Computer Science and Sustainability (pp. 1221-1235). (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings ; Vol. P-314). Gesellschaft für Informatik e.V.. https://doi.org/10.18420/informatik2021-101

Vancouver

Thiée LW. A systematic literature review of machine learning canvases. In Gesellschaft für Informatik e.V. (GI), editor, INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin: Computer Science and Sustainability. Bonn: Gesellschaft für Informatik e.V. 2021. p. 1221-1235. (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings ). doi: 10.18420/informatik2021-101

Bibtex

@inbook{f7b231c03980474da4fb70789ee5da24,
title = "A systematic literature review of machine learning canvases",
abstract = "The use of machine learning technology is still significantly lower in small and medium sized enterprises than in large enterprises. It seems that there are specific challenges in the implementation of data-driven methods, that hinder SMEs in their adoption. One approach to support the initialization and execution of such methods is the use of boundary objects, e.g., canvases, serving as a visual communication document. As it is not clear which approaches are being pursued in detail and how they are interrelated, in this paper, a systematic literature review is being presented, that identifies and analyzes 18 canvas artifacts. These canvases represent the status quo and they can be grouped into four distinct categories of different foci. The aggregation of the fields and questions provides an essence of canvas contents, to point out gaps and ultimately to expand the canvas approach as well as ML adoption.(Workshop: K{\"u}nstliche Intelligenz f{\"u}r kleine und mittlere Unternehmen (KI-KMU 2021)",
keywords = "Informatics, Machine Learning, Canvas, Literature Review, SME, Business informatics, Canvas, Literature Review, Machine Learning, SME",
author = "Lukas-Walter Thi{\'e}e",
year = "2021",
month = oct,
day = "5",
doi = "10.18420/informatik2021-101",
language = "English",
series = "GI-Edition: Lecture Notes in Informatics (LNI), Proceedings ",
publisher = "Gesellschaft f{\"u}r Informatik e.V.",
pages = "1221--1235",
editor = "{Gesellschaft f{\"u}r Informatik e.V. (GI)}",
booktitle = "INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin",
address = "Germany",
note = "51. Jahrestagung der Gesellschaft f{\"u}r Informatik - INFORMATIK 2021 ; Conference date: 27-09-2021 Through 01-10-2021",
url = "https://informatik2021.gi.de/",

}

RIS

TY - CHAP

T1 - A systematic literature review of machine learning canvases

AU - Thiée, Lukas-Walter

N1 - Conference code: 51

PY - 2021/10/5

Y1 - 2021/10/5

N2 - The use of machine learning technology is still significantly lower in small and medium sized enterprises than in large enterprises. It seems that there are specific challenges in the implementation of data-driven methods, that hinder SMEs in their adoption. One approach to support the initialization and execution of such methods is the use of boundary objects, e.g., canvases, serving as a visual communication document. As it is not clear which approaches are being pursued in detail and how they are interrelated, in this paper, a systematic literature review is being presented, that identifies and analyzes 18 canvas artifacts. These canvases represent the status quo and they can be grouped into four distinct categories of different foci. The aggregation of the fields and questions provides an essence of canvas contents, to point out gaps and ultimately to expand the canvas approach as well as ML adoption.(Workshop: Künstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2021)

AB - The use of machine learning technology is still significantly lower in small and medium sized enterprises than in large enterprises. It seems that there are specific challenges in the implementation of data-driven methods, that hinder SMEs in their adoption. One approach to support the initialization and execution of such methods is the use of boundary objects, e.g., canvases, serving as a visual communication document. As it is not clear which approaches are being pursued in detail and how they are interrelated, in this paper, a systematic literature review is being presented, that identifies and analyzes 18 canvas artifacts. These canvases represent the status quo and they can be grouped into four distinct categories of different foci. The aggregation of the fields and questions provides an essence of canvas contents, to point out gaps and ultimately to expand the canvas approach as well as ML adoption.(Workshop: Künstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2021)

KW - Informatics

KW - Machine Learning, Canvas

KW - Literature Review

KW - SME

KW - Business informatics

KW - Canvas

KW - Literature Review

KW - Machine Learning

KW - SME

UR - http://www.scopus.com/inward/record.url?scp=85127435035&partnerID=8YFLogxK

U2 - 10.18420/informatik2021-101

DO - 10.18420/informatik2021-101

M3 - Article in conference proceedings

T3 - GI-Edition: Lecture Notes in Informatics (LNI), Proceedings

SP - 1221

EP - 1235

BT - INFORMATIK 2021 - Die 51. Jahrestagung der Gesellschaft fur Informatikin

A2 - Gesellschaft für Informatik e.V. (GI),

PB - Gesellschaft für Informatik e.V.

CY - Bonn

T2 - 51. Jahrestagung der Gesellschaft für Informatik - INFORMATIK 2021

Y2 - 27 September 2021 through 1 October 2021

ER -

Other publications by the same author(s)

Ablation Study of a Multimodal Gat Network on Perfect Synthetic and Real-world Data to Investigate the Influence of Language Models in Invoice Recognition

Thiée, L. W., 11.09.2024, Document Analysis and Recognition – ICDAR 2024 Workshops: Athens, Greece, August 30–31, 2024 Proceedings, Part II. Mouchère, H. & Zhu, A. (eds.). Cham: Springer Nature AG, Vol. 2. p. 199-212 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14936)(Document analysis and recognition - ICDAR 2024 workshops ; vol. 2).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Extraction of information from invoices - challenges in the extraction pipeline

Thiée, L. W., Krieger, F. & Funk, B., 2023, INFORMATIK 2023: Designing Futures: Zukünfte gestalten, 26. – 29. September 2023, Berlin. Klein, M., Krupka, D., Winter, C. & Wohlgemuth, V. (eds.). Bonn: Gesellschaft für Informatik e.V., p. 1777-1792 16 p. (GI-Edition: Lecture Notes in Informatics (LNI), Proceedings; vol. P-337).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

DASC-PM v1.1: A Process Model for Data Science Projects

Schulz, M., Neuhaus, U., Kaufmann, J., Kühnel, S., Alekozai, E. M., Rohde, H., Hoseini, S., Theuerkauf, R., Badura, D., Kerzel, U., Lanquillon, C., Daurer, S., Günther, M., Huber, L., Thiée, L-W., Heiden, P. Z., Passlick, J., Dieckmann, J., Schwade, F., Seyffarth, T., Badewitz, W., Rissler, R., Sackmann, S., Gölzer, P., Welter, F., Röth, J., Seidelmann, J. & Haneke, U., 03.2022, Elmshorn: NORDAKADEMIE gAG Hochschule der Wirtschaft. 89 p.

Research output: Books and anthologies › Monographs › Research

Parking space management through deep learning – an approach for automated, low-cost and scalable real-time detection of parking space occupancy

Schulte, M. R., Thiée, L-W., Scharfenberger, J. & Funk, B., 11.2021, Innovation Through Information Systems - Volume II: A Collection of Latest Research on Technology Issues. Ahlemann, F., Schütte, R. & Stieglitz, S. (eds.). Cham: Springer Science and Business Media Deutschland GmbH, p. 642-655 14 p. (Lecture Notes in Information Systems and Organisation; vol. 47).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY

Thiée, L-W., Petrowsky, H. M., Frech, M-L., Loschelder, D. D. & Funk, B., 11.05.2021, ECIS 2021 Proceedings: Human Values Crisis in a Digitizing World. A. F. I. S. (ed.). AIS eLibrary, 1655

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Documents

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