The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]

Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from g...
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Autor*in:	Fala Cramond [verfasserIn] Alison O'Mara-Eves [verfasserIn] Lee Doran-Constant [verfasserIn] Andrew SC Rice [verfasserIn] Malcolm Macleod [verfasserIn] James Thomas [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Übergeordnetes Werk:	In: Wellcome Open Research - Wellcome, 2017, 3(2019)
Übergeordnetes Werk:	volume:3 ; year:2019

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.12688/wellcomeopenres.14738.3

Katalog-ID:	DOAJ047239948

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spelling	10.12688/wellcomeopenres.14738.3 doi (DE-627)DOAJ047239948 (DE-599)DOAJ360fbc70e68c41d499876f05fe2155f3 DE-627 ger DE-627 rakwb eng Fala Cramond verfasserin aut The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved] 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making. Medicine R Science Q Alison O'Mara-Eves verfasserin aut Lee Doran-Constant verfasserin aut Andrew SC Rice verfasserin aut Malcolm Macleod verfasserin aut James Thomas verfasserin aut In Wellcome Open Research Wellcome, 2017 3(2019) (DE-627)872620239 (DE-600)2874778-1 2398502X nnns volume:3 year:2019 https://doi.org/10.12688/wellcomeopenres.14738.3 kostenfrei https://doaj.org/article/360fbc70e68c41d499876f05fe2155f3 kostenfrei https://wellcomeopenresearch.org/articles/3-157/v3 kostenfrei https://doaj.org/toc/2398-502X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2019
allfields_unstemmed	10.12688/wellcomeopenres.14738.3 doi (DE-627)DOAJ047239948 (DE-599)DOAJ360fbc70e68c41d499876f05fe2155f3 DE-627 ger DE-627 rakwb eng Fala Cramond verfasserin aut The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved] 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making. Medicine R Science Q Alison O'Mara-Eves verfasserin aut Lee Doran-Constant verfasserin aut Andrew SC Rice verfasserin aut Malcolm Macleod verfasserin aut James Thomas verfasserin aut In Wellcome Open Research Wellcome, 2017 3(2019) (DE-627)872620239 (DE-600)2874778-1 2398502X nnns volume:3 year:2019 https://doi.org/10.12688/wellcomeopenres.14738.3 kostenfrei https://doaj.org/article/360fbc70e68c41d499876f05fe2155f3 kostenfrei https://wellcomeopenresearch.org/articles/3-157/v3 kostenfrei https://doaj.org/toc/2398-502X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2019
allfieldsGer	10.12688/wellcomeopenres.14738.3 doi (DE-627)DOAJ047239948 (DE-599)DOAJ360fbc70e68c41d499876f05fe2155f3 DE-627 ger DE-627 rakwb eng Fala Cramond verfasserin aut The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved] 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making. Medicine R Science Q Alison O'Mara-Eves verfasserin aut Lee Doran-Constant verfasserin aut Andrew SC Rice verfasserin aut Malcolm Macleod verfasserin aut James Thomas verfasserin aut In Wellcome Open Research Wellcome, 2017 3(2019) (DE-627)872620239 (DE-600)2874778-1 2398502X nnns volume:3 year:2019 https://doi.org/10.12688/wellcomeopenres.14738.3 kostenfrei https://doaj.org/article/360fbc70e68c41d499876f05fe2155f3 kostenfrei https://wellcomeopenresearch.org/articles/3-157/v3 kostenfrei https://doaj.org/toc/2398-502X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2019
allfieldsSound	10.12688/wellcomeopenres.14738.3 doi (DE-627)DOAJ047239948 (DE-599)DOAJ360fbc70e68c41d499876f05fe2155f3 DE-627 ger DE-627 rakwb eng Fala Cramond verfasserin aut The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved] 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making. Medicine R Science Q Alison O'Mara-Eves verfasserin aut Lee Doran-Constant verfasserin aut Andrew SC Rice verfasserin aut Malcolm Macleod verfasserin aut James Thomas verfasserin aut In Wellcome Open Research Wellcome, 2017 3(2019) (DE-627)872620239 (DE-600)2874778-1 2398502X nnns volume:3 year:2019 https://doi.org/10.12688/wellcomeopenres.14738.3 kostenfrei https://doaj.org/article/360fbc70e68c41d499876f05fe2155f3 kostenfrei https://wellcomeopenresearch.org/articles/3-157/v3 kostenfrei https://doaj.org/toc/2398-502X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 3 2019
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author	Fala Cramond
spellingShingle	Fala Cramond misc Medicine misc R misc Science misc Q The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
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topic_title	The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
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title	The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
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title_full	The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
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author_browse	Fala Cramond Alison O'Mara-Eves Lee Doran-Constant Andrew SC Rice Malcolm Macleod James Thomas
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author-letter	Fala Cramond
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title_sort	development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
title_auth	The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
abstract	Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.
abstractGer	Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.
abstract_unstemmed	Background: The extraction of data from the reports of primary studies, on which the results of systematic reviews depend, needs to be carried out accurately. To aid reliability, it is recommended that two researchers carry out data extraction independently. The extraction of statistical data from graphs in PDF files is particularly challenging, as the process is usually completely manual, and reviewers need sometimes to revert to holding a ruler against the page to read off values: an inherently time-consuming and error-prone process. Methods: To mitigate some of the above problems we integrated and customised two existing JavaScript libraries to create a new web-based graphical data extraction tool to assist reviewers in extracting data from graphs. This tool aims to facilitate more accurate and timely data extraction through a user interface which can be used to extract data through mouse clicks. We carried out a non-inferiority evaluation to examine its performance in comparison with participants’ standard practice for extracting data from graphs in PDF documents. Results: We found that the customised graphical data extraction tool is not inferior to users’ (N=10) prior standard practice. Our study was not designed to show superiority, but suggests that, on average, participants saved around 6 minutes per graph using the new tool, accompanied by a substantial increase in accuracy. Conclusions: Our study suggests that the incorporation of this type of tool in online systematic review software would be beneficial in facilitating the production of accurate and timely evidence synthesis to improve decision-making.
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title_short	The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]
url	https://doi.org/10.12688/wellcomeopenres.14738.3 https://doaj.org/article/360fbc70e68c41d499876f05fe2155f3 https://wellcomeopenresearch.org/articles/3-157/v3 https://doaj.org/toc/2398-502X
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author2	Alison O'Mara-Eves Lee Doran-Constant Andrew SC Rice Malcolm Macleod James Thomas
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score	7.4020357

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The development and evaluation of an online application to assist in the extraction of data from graphs for use in systematic reviews [version 3; referees: 3 approved]

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