Towards Increased Understanding of Open Data Use for Software Development
Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data reso...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Grzenda, Maciej [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Information systems frontiers - Springer US, 1999, 23(2019), 2 vom: 22. Nov., Seite 495-513 |
|---|---|
| Übergeordnetes Werk: |
volume:23 ; year:2019 ; number:2 ; day:22 ; month:11 ; pages:495-513 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10796-019-09954-6 |
|---|
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OLC212543539X |
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| 520 | |a Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. | ||
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10.1007/s10796-019-09954-6 doi (DE-627)OLC212543539X (DE-He213)s10796-019-09954-6-p DE-627 ger DE-627 rakwb eng 070 004 VZ 24,1 3,2 ssgn Grzenda, Maciej verfasserin (orcid)0000-0002-5440-4954 aut Towards Increased Understanding of Open Data Use for Software Development 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2019 Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. Open data Application development Application programming interface Big data Legierski, Jaroslaw aut Enthalten in Information systems frontiers Springer US, 1999 23(2019), 2 vom: 22. Nov., Seite 495-513 (DE-627)333991958 (DE-600)2057666-3 (DE-576)444637265 1387-3326 nnns volume:23 year:2019 number:2 day:22 month:11 pages:495-513 https://doi.org/10.1007/s10796-019-09954-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-BUB SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-BBI GBV_ILN_26 GBV_ILN_70 AR 23 2019 2 22 11 495-513 |
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10.1007/s10796-019-09954-6 doi (DE-627)OLC212543539X (DE-He213)s10796-019-09954-6-p DE-627 ger DE-627 rakwb eng 070 004 VZ 24,1 3,2 ssgn Grzenda, Maciej verfasserin (orcid)0000-0002-5440-4954 aut Towards Increased Understanding of Open Data Use for Software Development 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2019 Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. Open data Application development Application programming interface Big data Legierski, Jaroslaw aut Enthalten in Information systems frontiers Springer US, 1999 23(2019), 2 vom: 22. Nov., Seite 495-513 (DE-627)333991958 (DE-600)2057666-3 (DE-576)444637265 1387-3326 nnns volume:23 year:2019 number:2 day:22 month:11 pages:495-513 https://doi.org/10.1007/s10796-019-09954-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-BUB SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-BBI GBV_ILN_26 GBV_ILN_70 AR 23 2019 2 22 11 495-513 |
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10.1007/s10796-019-09954-6 doi (DE-627)OLC212543539X (DE-He213)s10796-019-09954-6-p DE-627 ger DE-627 rakwb eng 070 004 VZ 24,1 3,2 ssgn Grzenda, Maciej verfasserin (orcid)0000-0002-5440-4954 aut Towards Increased Understanding of Open Data Use for Software Development 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2019 Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. Open data Application development Application programming interface Big data Legierski, Jaroslaw aut Enthalten in Information systems frontiers Springer US, 1999 23(2019), 2 vom: 22. Nov., Seite 495-513 (DE-627)333991958 (DE-600)2057666-3 (DE-576)444637265 1387-3326 nnns volume:23 year:2019 number:2 day:22 month:11 pages:495-513 https://doi.org/10.1007/s10796-019-09954-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-BUB SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-BBI GBV_ILN_26 GBV_ILN_70 AR 23 2019 2 22 11 495-513 |
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Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. © The Author(s) 2019 |
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Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. © The Author(s) 2019 |
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Abstract The way open data resources of varied type and volume are used by software applications remains only partly known. In this study, following CRoss-Industry Standard Process for Data Mining, we propose a methodology for collecting and analyzing access data describing the use of open data resources by individual software applications. The methodology includes novel categorization of the data collected at an exposition portal providing access to underlying open data portals and third-party services. Furthermore, it enables research into the use of both different open data resources and resource groups such as Big Data resources for software development. We apply the methodology to analyze the re-use of open urban data during reference software development events. The identification of open data use by individual applications is largely improved compared to baseline scenario, as shown by numerical indicators including F1 measure. Insight into re-use of data streams and actual development time is obtained. © The Author(s) 2019 |
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333991958 |
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n |
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false |
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false |
| doi_str |
10.1007/s10796-019-09954-6 |
| up_date |
2024-07-04T03:41:03.322Z |
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1803618314692329472 |
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