Sites:WWW/Tools/ORKG/page - Revision history

Bootsa: add links (have to use full URLs so looks like external links)

2024-11-27T10:29:52Z

add links (have to use full URLs so looks like external links)

Bootsa: change hypothesis evidence explorer link to subdomain

2024-11-27T10:19:06Z

change hypothesis evidence explorer link to subdomain

← Older revision		Revision as of 12:19, 27 November 2024
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	As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:		As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:

	[https://~~maudbernardverdier.shinyapps.io/Hypothesis~~-evidence-explorer/ Hypothesis evidence explorer]		[https://hypothesis-evidence-explorer.hi-knowledge.org/ Hypothesis evidence explorer]

	=== Example application: Teaching ecology ===		=== Example application: Teaching ecology ===

Bootsa: Bootsa moved page Sites:Tools-ORKG-page to Sites:WWW/Tools/ORKG/page without leaving a redirect: Reorganise

2024-11-20T11:06:34Z

Bootsa moved page Sites:Tools-ORKG-page to Sites:WWW/Tools/ORKG/page without leaving a redirect: Reorganise

← Older revision	Revision as of 13:06, 20 November 2024
(No difference)

Bootsa: /* Semantic annotation of literature using ORKG */

2024-09-06T11:33:18Z

Semantic annotation of literature using ORKG

JonathanJeschke: /* Description: */

2024-07-18T07:15:45Z

Description:

← Older revision		Revision as of 09:15, 18 July 2024
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	Open platform, templates and database for community-curated and FAIR semantic annotation of the scientific literature. Find out more at: [https://orkg.org orkg.org]		Open platform, templates and database for community-curated and FAIR semantic annotation of the scientific literature. Find out more at: [https://orkg.org orkg.org]

	The ORKG is a public project hosted by [https://www.tib.eu/en/ TiB Leibniz Information Center for Science and Technology University Library]		The Open Research Knowledge Graph (ORKG) is a public project hosted by [https://www.tib.eu/en/ TiB Leibniz Information Center for Science and Technology University Library]

	== Purpose: ==		== Purpose: ==

JonathanJeschke: /* Semantic annotation of literature using Open Knowledge Research Graph */

2024-07-18T07:13:42Z

Semantic annotation of literature using Open Knowledge Research Graph

← Older revision		Revision as of 09:13, 18 July 2024
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	= Semantic annotation of literature using ~~Open Knowledge Research Graph~~ =		= Semantic annotation of literature using ORKG =

	== Description: ==		== Description: ==

87.77.165.142: /* Example application: On-demand interactive synthesis for invasion biology */

2024-06-24T13:32:58Z

Example application: On-demand interactive synthesis for invasion biology

← Older revision		Revision as of 15:32, 24 June 2024
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	As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:		As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:

	[https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]		[https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]

87.77.165.142: /* Example application: On-demand interactive synthesis for invasion biology */

2024-06-24T13:31:43Z

Example application: On-demand interactive synthesis for invasion biology

← Older revision		Revision as of 15:31, 24 June 2024
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	As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:		As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the webapp here:
	* [https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]		[https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]
	* [https://on-demand-analyses.hi-knowledge.org/ On demand analyses]

	== Example application: Teaching ecology ==		== Example application: Teaching ecology ==

87.77.165.142: /* About */

2024-06-24T13:29:14Z

About

← Older revision		Revision as of 15:29, 24 June 2024
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	== About ==		== About ==

	Authors are the best people to tell us what their study and data are about, and they do it very well for humans reading their papers. However, there is no standardised ~~way~~ to summarise essential characteristics of papers in a way that is machine interpretable and interoperable. Huge efforts have been made to standardise metadata for datasets (e.g. EML), or to standardise bibliometric information, but nothing for annotating the scientific scope and knowledge contained in publications themselves.		Authors are the best people to tell us what their study and data are about, and they do it very well for humans reading their papers. However, there is no standardised approach to summarise essential characteristics of papers in a way that is machine interpretable and interoperable. Huge efforts have been made to standardise metadata for datasets (e.g. EML), or to standardise bibliometric information, but nothing for annotating the scientific scope and knowledge contained in publications themselves.

	The ORKG makes scientific knowledge human- and machine-actionable and thus enables completely new ways of machine assistance. With the ORKG, authors, but also readers assembling papers for a meta-analysis for instance, can annotate the scientific scope and content of studies. This will help researchers find relevant contributions to their field and create state-of-the-art comparisons and reviews.		The ORKG makes scientific knowledge human- and machine-actionable and thus enables completely new ways of machine assistance. With the ORKG, authors, but also readers assembling papers for a meta-analysis for instance, can annotate the scientific scope and content of studies. This will help researchers find relevant contributions to their field and create state-of-the-art comparisons and reviews.

87.77.165.142: /* Purpose: */

2024-06-24T13:27:46Z

Purpose:

← Older revision		Revision as of 15:27, 24 June 2024
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	* Add your own papers and annotate them in a machine-interpretable way to increase findability and re-use of your work		* Add your own papers and annotate them in a machine-interpretable way to increase findability and re-use of your work
	* Use the ORKG templates to systematically annotate papers for a meta-analysis		* Use the ORKG templates to systematically annotate papers for meta-analysis
	* Create on-demand interactive syntheses of the literature		* Create on-demand interactive syntheses of the literature

← Older revision		Revision as of 12:29, 27 November 2024
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	=== ORKG templates for Ecology and Invasion Biology ===		=== ORKG templates for Ecology and Invasion Biology ===

	In collaboration with the ORKG, we established a set of semantic templates to guide ecologists in annotating papers in a machine-interpretable and standardised way. We built these templates in an iterative process in a series of Hi Knowledge workshops ~~(<u>LINKS to workshops</u>)~~.		In collaboration with the ORKG, we established a set of semantic templates to guide ecologists in annotating papers in a machine-interpretable and standardised way. We built these templates in an iterative process in a series of [https://www.hi-knowledge.org/events Hi Knowledge workshops].

	Semantic templates promise:		Semantic templates promise:
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	These templates range from a very broad ecological scoping of a study ('''#1'''), similar to what is usually included in a publication's keywords, to more detailed description of study systems ('''#2''') and study designs ('''#3''').		These templates range from a very broad ecological scoping of a study ('''#1'''), similar to what is usually included in a publication's keywords, to more detailed description of study systems ('''#2''') and study designs ('''#3''').

	We also designed templates specific to invasion biology studies. The first ('''#4''') is a general description of the main theme, research questions, hypotheses and invasive taxa investigated, following our current conceptual scheme for invasion biology ~~(<u>internal link to tool)</u>~~. The second ('''#3''') describes the testing of major hypotheses in the field (described by template '''#6'''). It provides information about support or rebuttal of those hypotheses, in the same way as the Hi Knowledge data provided ~~(<u>internal link to hyp network</u>)~~.		We also designed templates specific to invasion biology studies. The first ('''#4''') is a general description of the main theme, research questions, hypotheses and invasive taxa investigated, following our current [https://www.hi-knowledge.org/tools/classification-scheme conceptual scheme for invasion biology]. The second ('''#3''') describes the testing of major hypotheses in the field (described by template '''#6'''). It provides information about support or rebuttal of those hypotheses, in the same way as the [https://www.hi-knowledge.org/tools/hypothesis-networks Hi Knowledge data] provided.

	'''Table 1:''' ORKG templates created for ecology studies, with #4-6 being specific to invasion biology.		'''Table 1:''' ORKG templates created for ecology studies, with #4-6 being specific to invasion biology.
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	If you think these templates are insufficient and want to create a template for your field or a particular research question, get started [https://orkg.org/about/19/Templates here].		If you think these templates are insufficient and want to create a template for your field or a particular research question, get started [https://orkg.org/about/19/Templates here].


	=== Example application: On-demand interactive synthesis for invasion biology ===		=== Example application: On-demand interactive synthesis for invasion biology ===
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	Annotations in the ORKG can be [https://orkg.org/data extracted] and used to build interactive syntheses and visualisations on a topic of interest. The easiest way to do this is to first build a comparison table across papers, choose which properties should be compared, and extract this structured data to be ingested in an R shiny app or Jupyter notebook.		Annotations in the ORKG can be [https://orkg.org/data extracted] and used to build interactive syntheses and visualisations on a topic of interest. The easiest way to do this is to first build a comparison table across papers, choose which properties should be compared, and extract this structured data to be ingested in an R shiny app or Jupyter notebook.

	As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the ~~webapp~~ here:		As a proof-of-concept, we created an R shiny app from ORKG annotations for the Hi Knowledge dataset on 10 major hypotheses in invasion biology (Jeschke & Heger, 2018). Explore the web app here:

	[https://hypothesis-evidence-explorer.hi-knowledge.org/ Hypothesis evidence explorer]		[https://hypothesis-evidence-explorer.hi-knowledge.org/ Hypothesis evidence explorer]

← Older revision		Revision as of 13:33, 6 September 2024
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	= Semantic annotation of literature using ORKG =		== Semantic annotation of literature using ORKG ==

	== Description: ==		=== Description: ===

	Open platform, templates and database for community-curated and FAIR semantic annotation of the scientific literature. Find out more at: [https://orkg.org orkg.org]		Open platform, templates and database for community-curated and FAIR semantic annotation of the scientific literature. Find out more at: [https://orkg.org orkg.org]
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	The Open Research Knowledge Graph (ORKG) is a public project hosted by [https://www.tib.eu/en/ TiB Leibniz Information Center for Science and Technology University Library]		The Open Research Knowledge Graph (ORKG) is a public project hosted by [https://www.tib.eu/en/ TiB Leibniz Information Center for Science and Technology University Library]

	== Purpose: ==		=== Purpose: ===

	* Add your own papers and annotate them in a machine-interpretable way to increase findability and re-use of your work		* Add your own papers and annotate them in a machine-interpretable way to increase findability and re-use of your work
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	* Create on-demand interactive syntheses of the literature		* Create on-demand interactive syntheses of the literature

	== About ==		=== About ===

	Authors are the best people to tell us what their study and data are about, and they do it very well for humans reading their papers. However, there is no standardised approach to summarise essential characteristics of papers in a way that is machine interpretable and interoperable. Huge efforts have been made to standardise metadata for datasets (e.g. EML), or to standardise bibliometric information, but nothing for annotating the scientific scope and knowledge contained in publications themselves.		Authors are the best people to tell us what their study and data are about, and they do it very well for humans reading their papers. However, there is no standardised approach to summarise essential characteristics of papers in a way that is machine interpretable and interoperable. Huge efforts have been made to standardise metadata for datasets (e.g. EML), or to standardise bibliometric information, but nothing for annotating the scientific scope and knowledge contained in publications themselves.
Line 19:		Line 19:
	The ORKG makes scientific knowledge human- and machine-actionable and thus enables completely new ways of machine assistance. With the ORKG, authors, but also readers assembling papers for a meta-analysis for instance, can annotate the scientific scope and content of studies. This will help researchers find relevant contributions to their field and create state-of-the-art comparisons and reviews.		The ORKG makes scientific knowledge human- and machine-actionable and thus enables completely new ways of machine assistance. With the ORKG, authors, but also readers assembling papers for a meta-analysis for instance, can annotate the scientific scope and content of studies. This will help researchers find relevant contributions to their field and create state-of-the-art comparisons and reviews.

	== ORKG templates for Ecology and Invasion Biology ==		=== ORKG templates for Ecology and Invasion Biology ===

	In collaboration with the ORKG, we established a set of semantic templates to guide ecologists in annotating papers in a machine-interpretable and standardised way. We built these templates in an iterative process in a series of Hi Knowledge workshops (<u>LINKS to workshops</u>).		In collaboration with the ORKG, we established a set of semantic templates to guide ecologists in annotating papers in a machine-interpretable and standardised way. We built these templates in an iterative process in a series of Hi Knowledge workshops (<u>LINKS to workshops</u>).
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	If you think these templates are insufficient and want to create a template for your field or a particular research question, get started [https://orkg.org/about/19/Templates here].		If you think these templates are insufficient and want to create a template for your field or a particular research question, get started [https://orkg.org/about/19/Templates here].

	== Example application: On-demand interactive synthesis for invasion biology ==		=== Example application: On-demand interactive synthesis for invasion biology ===

	Annotations in the ORKG can be [https://orkg.org/data extracted] and used to build interactive syntheses and visualisations on a topic of interest. The easiest way to do this is to first build a comparison table across papers, choose which properties should be compared, and extract this structured data to be ingested in an R shiny app or Jupyter notebook.		Annotations in the ORKG can be [https://orkg.org/data extracted] and used to build interactive syntheses and visualisations on a topic of interest. The easiest way to do this is to first build a comparison table across papers, choose which properties should be compared, and extract this structured data to be ingested in an R shiny app or Jupyter notebook.
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	[https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]		[https://maudbernardverdier.shinyapps.io/Hypothesis-evidence-explorer/ Hypothesis evidence explorer]

	== Example application: Teaching ecology ==		=== Example application: Teaching ecology ===


	[https://orkg.org/list/R674168/ ORKG list - Class assignment: annotating papers in invasion biology]		[https://orkg.org/list/R674168/ ORKG list - Class assignment: annotating papers in invasion biology]