Sankey Diagram - Revision history

S203379: /* Conclusion */

2022-03-22T09:04:41Z

Conclusion

← Older revision		Revision as of 09:04, 22 March 2022
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	The diagram is versatile and can be applied to different scenarios to visualize completely distinct insights. However, the versatility of the diagram does have limitations when it comes to the traceability of the process. If a specific iteration needs to be studied to understand its causes, the diagram does a poor job at tracing. As information is generalized in the flows, an individual data point cannot be identified directly on the diagram. To obtain a trace of resource involvement the dataset used to create the diagram would have to be picked apart to find the path taken from origin point to endpoint.		The diagram is versatile and can be applied to different scenarios to visualize completely distinct insights. However, the versatility of the diagram does have limitations when it comes to the traceability of the process. If a specific iteration needs to be studied to understand its causes, the diagram does a poor job at tracing. As information is generalized in the flows, an individual data point cannot be identified directly on the diagram. To obtain a trace of resource involvement the dataset used to create the diagram would have to be picked apart to find the path taken from origin point to endpoint.

			Even though the diagram was created in 1898, it has recently gathered attention in the last decade. This has led to the development of new applications adapted to the study line it is applied to. The application that has picked my interest is that in risk management, this application has the potential to create benefits and savings for project/program/portfolio managers. In many cases, managers must take an either-or decision, a risk Sankey diagram could help them make the decision by prioritizing the action that could have the most negative direct/indirect impact on the project. This application does require a more extensive study of risk as the direct and indirect impacts have to be identified/studied to deliver the benefits of the risk Sankey diagram insight. It could be argued that the time spent developing this data could be more costly than the effects of the indirect impacts a traditional Risk management assessment would ignore, and therefore it is important to assess the level of uncertainty a project has to determine if superficial risk management or if a more extensive application is needed.

	= Annotated Bibliography =		= Annotated Bibliography =

S203379: /* Analyzing Hierarchy type data */

2022-03-22T08:40:07Z

Analyzing Hierarchy type data

← Older revision		Revision as of 08:40, 22 March 2022
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	== Analyzing Hierarchy type data <ref name="Dave" /> ==		== Analyzing Hierarchy type data <ref name="Dave" /> ==
	[[File:Sankey5.png\|400px\|thumb\|right\|Hierarchy Sankey Diagram <ref name="Dave" />]] In Dave's article, he describes the Hierarchy Sankey diagram as a flow diagram that follows hierarchy type data. What this means is that the data must follow a specific order and it must not mix one type with the other at the same level in the diagram. For example, in his article, Dave explains that he is provided with a dataset on African mobile distribution. This dataset provides the country, city, region, segment, sales, and profits. The data is classified as hierarchical and it must follow the order of the country first, then the city, and finally the segment. This hierarchy formulation makes it easier to compare data between its equals. In the example diagram, it is clear that Nigeria is the country with the most mobile users while Liberia is the country with the least mobile users. At a city level, it can be concluded that all the African cities have a quite different distribution when splitting into the three segments, but there is a clear preference for one of the segments over the others. While at the segment level there is not much overall difference between the three options. What can be taken from the diagram is that each mobile segment can identify what parts of the African continent require their services and invest more heavily in the infrastructure to expand their market.		[[File:Sankey5.png\|400px\|thumb\|right\|Hierarchy Sankey Diagram <ref name="Dave" />]] In Dave's article, he describes the Hierarchy Sankey diagram as a flow diagram that follows hierarchy type data. What this means is that the data must follow a specific order and it must not mix one type with the other at the same level in the diagram. For example, in his article, Dave explains that he is provided with a dataset on African mobile distribution. This dataset provides the country, city, region, segment, sales, and profits. The data is classified as hierarchical and it must follow the order of the country first, then the city, and finally the segment. This hierarchy formulation makes it easier to compare data between its equals. In the example diagram, it is clear that Nigeria is the country with the most mobile users while Liberia is the country with the least mobile users. At a city level, it can be concluded that all the African cities have a quite different distribution when splitting into the three segments, but there is a clear preference for one of the segments over the others. While at the segment level there is not much overall difference between the three options. What can be taken from the diagram is that each mobile segment can identify what parts of the African continent require their services and invest more heavily in the infrastructure to expand their market. In terms of the Sankey Diagram application, it can be concluded that in most cases Sankey Diagrams will follow and visualize hierarchical data. This is as processes tend to follow a structured flow and dependencies are specified between actions, data must enter and exit in a specific place.

	== Quick trick to replace Machine-learning <ref name="Dave" /> ==		== Quick trick to replace Machine-learning <ref name="Dave" /> ==

S203379: /* Quick trick to replace Machine-learning */

2022-03-22T08:33:41Z

Quick trick to replace Machine-learning

← Older revision		Revision as of 08:33, 22 March 2022
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	== Quick trick to replace Machine-learning <ref name="Dave" /> ==		== Quick trick to replace Machine-learning <ref name="Dave" /> ==
	[[File:Sankey6.png\|~~500px~~\|thumb\|left\|Machine-learning Sankey Diagram <ref name="Dave" />]] In his article Dave makes a bold statement that Sankey diagrams are able to replace Machine learning to a certain degree. Machine learning at its core is used to analyze multiple inputs and outputs and identify patterns from the data.		[[File:Sankey6.png\|510px\|thumb\|left\|Machine-learning Sankey Diagram <ref name="Dave" />]] In his article Dave makes a bold statement that Sankey diagrams are able to replace Machine learning to a certain degree. Machine learning at its core is used to analyze multiple inputs and outputs and identify patterns from the data.

S203379: /* Quick trick to replace Machine-learning */

2022-03-22T08:28:57Z

Quick trick to replace Machine-learning

← Older revision		Revision as of 08:28, 22 March 2022
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	== Quick trick to replace Machine-learning <ref name="Dave" /> ==		== Quick trick to replace Machine-learning <ref name="Dave" /> ==
	[[File:Sankey6.png\|~~400px~~\|thumb\|left\|Machine-learning Sankey Diagram <ref name="Dave" />]] In his article Dave makes a bold statement that Sankey diagrams are able to replace Machine learning to a certain degree. Machine learning at its core is used to analyze multiple inputs and outputs and identify patterns from the data.		[[File:Sankey6.png\|500px\|thumb\|left\|Machine-learning Sankey Diagram <ref name="Dave" />]] In his article Dave makes a bold statement that Sankey diagrams are able to replace Machine learning to a certain degree. Machine learning at its core is used to analyze multiple inputs and outputs and identify patterns from the data.

S203379: /* Abstract */

2022-03-22T08:28:40Z

Abstract

← Older revision		Revision as of 08:28, 22 March 2022
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	= Abstract =		= Abstract =
	[[File:Sankey1898.png\|~~300px~~\|thumb\|right\|Captain Sankey's 1898 Steam engine diagram<ref name="original">"[https://zenodo.org/record/2036163#.YggSQurMK3A]", Kennedy, A. B. W. (1898, January 1). The Thermal Efficiency of Steam Engines. Report of the Committee Appointed to the Council Upon the Subject of the Definition of a Standard or Standards of Thermal Efficiency for Steam Engines: With an Introductory Note. (Including Appendixes and Plate at Back of Volume). Zenodo. Retrieved February 12, 2022, from https://zenodo.org/record/2036163#.YiT1WujMK3B</ref>]] Within project & portfolio management it has become even more important that leadership is able to visualize where resources are being allocated and used. This is in terms of simple supervision over the projects, but also to optimize the limited resources an organization has. The Sankey diagrams are a graphical way of visualizing the flow of resources in a team, project, process, company, etc. Resources mapped in a Sankey diagram can be anything from materials, monetary funds, people allocation, activities, etc. The Sankey diagram also takes into consideration the different dimensions of the components that are needed <ref>"[https://www-scopus-com.proxy.findit.cvt.dk/record/display.uri?eid=2-s2.0-85047938959&origin=inward&txGid=0704dcd764625e4d68c1a1fdd358989d&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT%3A1&retries=1&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1]",Vosough, Z., Kammer, D., Keck, M., & Groh, R. (2018). Mirroring sankey diagrams for visual comparison tasks. Paper presented at the VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3 349-355. doi:10.5220/0006651203490355 Retrieved from www.scopus.com</ref>, as resources do not always stay pure or unchanged. On many occasions, a resource can undergo a transformation due to a process being applied or the mix between resources creating a completely new component.		[[File:Sankey1898.png\|320px\|thumb\|right\|Captain Sankey's 1898 Steam engine diagram<ref name="original">"[https://zenodo.org/record/2036163#.YggSQurMK3A]", Kennedy, A. B. W. (1898, January 1). The Thermal Efficiency of Steam Engines. Report of the Committee Appointed to the Council Upon the Subject of the Definition of a Standard or Standards of Thermal Efficiency for Steam Engines: With an Introductory Note. (Including Appendixes and Plate at Back of Volume). Zenodo. Retrieved February 12, 2022, from https://zenodo.org/record/2036163#.YiT1WujMK3B</ref>]] Within project & portfolio management it has become even more important that leadership is able to visualize where resources are being allocated and used. This is in terms of simple supervision over the projects, but also to optimize the limited resources an organization has. The Sankey diagrams are a graphical way of visualizing the flow of resources in a team, project, process, company, etc. Resources mapped in a Sankey diagram can be anything from materials, monetary funds, people allocation, activities, etc. The Sankey diagram also takes into consideration the different dimensions of the components that are needed <ref>"[https://www-scopus-com.proxy.findit.cvt.dk/record/display.uri?eid=2-s2.0-85047938959&origin=inward&txGid=0704dcd764625e4d68c1a1fdd358989d&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT%3A1&retries=1&featureToggles=FEATURE_NEW_DOC_DETAILS_EXPORT:1]",Vosough, Z., Kammer, D., Keck, M., & Groh, R. (2018). Mirroring sankey diagrams for visual comparison tasks. Paper presented at the VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3 349-355. doi:10.5220/0006651203490355 Retrieved from www.scopus.com</ref>, as resources do not always stay pure or unchanged. On many occasions, a resource can undergo a transformation due to a process being applied or the mix between resources creating a completely new component.

S203379 at 08:28, 22 March 2022

2022-03-22T08:28:25Z

← Older revision		Revision as of 08:28, 22 March 2022
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	The article's aim is to highlight the usefulness of the Sankey diagram in a project & portfolio management context. The article includes a discussion of the diagram's pros and cons from the Managements perspective.		The article's aim is to highlight the usefulness of the Sankey diagram in a project & portfolio management context. The article includes a discussion of the diagram's pros and cons from the Managements perspective.

	[[File:Sankey_Diagrams_01.png\|~~450px~~\|thumb\|right\|Sankey diagram of flow of information between countries<ref>"[https://www.originlab.com/doc/Origin-Help/Sankey-Diagram]", OriginLab (2021). 28.9.24 Sankey Diagrams. https://www.originlab.com/doc/Origin-Help/Sankey-Diagram</ref>]]		[[File:Sankey_Diagrams_01.png\|470px\|thumb\|right\|Sankey diagram of flow of information between countries<ref>"[https://www.originlab.com/doc/Origin-Help/Sankey-Diagram]", OriginLab (2021). 28.9.24 Sankey Diagrams. https://www.originlab.com/doc/Origin-Help/Sankey-Diagram</ref>]]
	__TOC__		__TOC__

S203379: /* Annotated Bibliography */

2022-03-22T08:25:20Z

Annotated Bibliography

← Older revision		Revision as of 08:25, 22 March 2022
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	In this section, references have been provided for further reading on the topic of the use of Sankey Diagrams in different lines of study.		In this section, references have been provided for further reading on the topic of the use of Sankey Diagrams in different lines of study.

	* Otto, E., Culakova, E., Meng, S., Zhang, Z., Xu, H., Mohile, S., & Flannery, M. A. (2022, January 6). ''Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer''. ELSEVIER.		* Otto, E., Culakova, E., Meng, S., Zhang, Z., Xu, H., Mohile, S., & Flannery, M. A. (2022, January 6). ''Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer''. ELSEVIER. https://doi.org/10.1016/j.jgo.2021.12.017
	**The article is useful to those who are looking for further explanation of the implementation of Sankey Diagrams to visualize patterns between the data. Even though the article is focused on the implementation of the diagram in a medical setting, the example of identifying patterns between the people observed can easily be transposed with data from employee productivity depending on the amount of time they have working in the same company.		**The article is useful to those who are looking for further explanation of the implementation of Sankey Diagrams to visualize patterns between the data. Even though the article is focused on the implementation of the diagram in a medical setting, the example of identifying patterns between the people observed can easily be transposed with data from employee productivity depending on the amount of time they have working in the same company.

S203379: /* Annotated Bibliography */

2022-03-22T08:23:03Z

Annotated Bibliography

← Older revision		Revision as of 08:23, 22 March 2022
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	* Otto, E., Culakova, E., Meng, S., Zhang, Z., Xu, H., Mohile, S., & Flannery, M. A. (2022, January 6). ''Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer''. ELSEVIER.		* Otto, E., Culakova, E., Meng, S., Zhang, Z., Xu, H., Mohile, S., & Flannery, M. A. (2022, January 6). ''Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer''. ELSEVIER.
	**The article is useful to those who are looking for further explanation of the implementation of Sankey Diagrams to visualize patterns between the data. Even though the article is focused on the implementation of the diagram in a medical setting, the example of identifying patterns between the people observed can easily be transposed with data from employee productivity depending on the amount of time they have working in the same company.		**The article is useful to those who are looking for further explanation of the implementation of Sankey Diagrams to visualize patterns between the data. Even though the article is focused on the implementation of the diagram in a medical setting, the example of identifying patterns between the people observed can easily be transposed with data from employee productivity depending on the amount of time they have working in the same company.


			*Romão, M. L., & Correia, P. M. A. R. (2021). New Eyes for an Old Challenge: How the Portuguese Ministry of Justice is Using Sankey Diagrams to Improve Knowledge on the Judicial System Dynamics. International Journal for Court Administration, 12(1). https://doi.org/10.36745/ijca.335
			**The article focuses on the benefits the use of the Sankey Diagram had for the Portuguese Justice system. By using the diagram, the Ministry of Justice was able to give participants a better understanding of the justice system. The overview taken in this article is a good example of a program/portfolio application of the Sankey Diagram in real life.

	= References =		= References =
	<references/>		<references/>

S203379 at 09:02, 15 March 2022

2022-03-15T09:02:07Z

← Older revision		Revision as of 09:02, 15 March 2022
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	The article's aim is to highlight the usefulness of the Sankey diagram in a project & portfolio management context. The article includes a discussion of the diagram's pros and cons from the Managements perspective.		The article's aim is to highlight the usefulness of the Sankey diagram in a project & portfolio management context. The article includes a discussion of the diagram's pros and cons from the Managements perspective.

	[[File:Sankey_Diagrams_01.png\|~~500px~~\|thumb\|right\|Sankey diagram of flow of information between countries<ref>"[https://www.originlab.com/doc/Origin-Help/Sankey-Diagram]", OriginLab (2021). 28.9.24 Sankey Diagrams. https://www.originlab.com/doc/Origin-Help/Sankey-Diagram</ref>]]		[[File:Sankey_Diagrams_01.png\|450px\|thumb\|right\|Sankey diagram of flow of information between countries<ref>"[https://www.originlab.com/doc/Origin-Help/Sankey-Diagram]", OriginLab (2021). 28.9.24 Sankey Diagrams. https://www.originlab.com/doc/Origin-Help/Sankey-Diagram</ref>]]
	__TOC__		__TOC__

S203379: /* Analyzing Hierarchy type data */

2022-03-15T09:01:56Z

Analyzing Hierarchy type data

← Older revision		Revision as of 09:01, 15 March 2022
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	== Analyzing Hierarchy type data <ref name="Dave" /> ==		== Analyzing Hierarchy type data <ref name="Dave" /> ==
	[[File:Sankey5.png\|~~300px~~\|thumb\|~~left~~\|Hierarchy Sankey Diagram <ref name="Dave" />]] In Dave's article, he describes the Hierarchy Sankey diagram as a flow diagram that follows hierarchy type data. What this means is that the data must follow a specific order and it must not mix one type with the other at the same level in the diagram. For example, in his article, Dave explains that he is provided with a dataset on African mobile distribution. This dataset provides the country, city, region, segment, sales, and profits. The data is classified as hierarchical and it must follow the order of the country first, then the city, and finally the segment. This hierarchy formulation makes it easier to compare data between its equals. In the example diagram, it is clear that Nigeria is the country with the most mobile users while Liberia is the country with the least mobile users. At a city level, it can be concluded that all the African cities have a quite different distribution when splitting into the three segments, but there is a clear preference for one of the segments over the others. While at the segment level there is not much overall difference between the three options. What can be taken from the diagram is that each mobile segment can identify what parts of the African continent require their services and invest more heavily in the infrastructure to expand their market.		[[File:Sankey5.png\|400px\|thumb\|right\|Hierarchy Sankey Diagram <ref name="Dave" />]] In Dave's article, he describes the Hierarchy Sankey diagram as a flow diagram that follows hierarchy type data. What this means is that the data must follow a specific order and it must not mix one type with the other at the same level in the diagram. For example, in his article, Dave explains that he is provided with a dataset on African mobile distribution. This dataset provides the country, city, region, segment, sales, and profits. The data is classified as hierarchical and it must follow the order of the country first, then the city, and finally the segment. This hierarchy formulation makes it easier to compare data between its equals. In the example diagram, it is clear that Nigeria is the country with the most mobile users while Liberia is the country with the least mobile users. At a city level, it can be concluded that all the African cities have a quite different distribution when splitting into the three segments, but there is a clear preference for one of the segments over the others. While at the segment level there is not much overall difference between the three options. What can be taken from the diagram is that each mobile segment can identify what parts of the African continent require their services and invest more heavily in the infrastructure to expand their market.

	== Quick trick to replace Machine-learning <ref name="Dave" /> ==		== Quick trick to replace Machine-learning <ref name="Dave" /> ==