In understanding the larger history of Data Visualization starting from tables dating back to 2C to the advent of Chord Diagrams in 2009, it is clear that human beings’ concern around best information recording practices has been and is an ongoing process. As understanding data is increasingly becoming important not just for businesses but for everyone, there is a heated race to provide the best Data Visualization tools. Particularly in the day and age where global health crisis is also a global information crises (Xie, et al., 2020), tools that efficiently, effectively, and accurately portray insights are critical in helping people without subject matter expertise access and understand information they need. But what exact tools are out there that professionals and non-professionals utilize today in 2020? When did these tools emerge? How are these tools relevant in the realm of modern data visualization? The resulting timeline from this research intends to expand on the three questions, presenting a somewhat brief history of modern data visualization programs.
Three different existing visualizations were referenced in creating the timeline.
The first reference was Milestones in the history of thematic cartography, statistical graphics, and data visualization by Friendly, M. & Denis, D. J. (2001). I found that the visualization was easy to follow thanks to the color-coded categorization of each events. However, users would be directed to another page in order to view further details for an event instead of having all the details in the pop-up module, a design that I found to be an interference in allowing for a smooth interaction with the timeline.
The second reference was The Dawn Wall: El Capitan’s Most Unwelcoming Route by Carter, S., Andrews, A., Watkins D. & Ward, J. (2015). Although I wasn’t able to find action-simulating, sequential background images for my timeline, I thought that the use of media that helped users visualize the description helped facilitate the overall information communication.
The third reference was Timeline: AMERICAN PRINTS 1960 TO NOW by Wang, X. (2019). Two observations were made here. First, the consistency in image sizes and description length (4-5 sentences) helped the user be able to focus on the content itself. Secondly, a darker background seemed more apt when showing images that sit on the lighter end of the color spectrum. The darker background allows for a clear delineation of where the image sits and the text boxes are, providing the visualization a more structured feel.
To visualize my findings, I used TimelineJS, a web-based tool created by knight lab that facilitates efficient and templated timeline creation. The platform provides a pre-made Google Spreadsheets template that has a relatively low flexibility in terms of customization. Columns were fixed with necessary data columns and few select aesthetic adjustment options.
I utilized Google for research, a perhaps obvious choice as a predominant search engine, to scavenge articles on modern data visualization software. Most data were taken from articles and respective platform’s websites. Details on exact sources can be found in subsequent sections and in my citations.
Research and Visualization Methodology
I compiled the list of known Data Visualization tools from five different sources: a 2017 Forbes article, a 2020 Forbes article, a 2020 GeeksforGeeks article, a 2020 PC Mag report, and a 2020 Capterra report. Tallying up the number of times a tool was mentioned across the five platforms, I selected five tools that were mentioned the most and subjectively added four (Klipfolio, Excel, Paraview, and DataWrapper) as I found them interesting. I also could not locate v.1.0 release notes or articles for some tools, which made it impossible to create a timeline for such data without launch-date information. I collected and drafted information for details using the same articles mentioned above and via respective company websites.
In terms of the visualizing the collected information, I input the relevant information in chronological order into the Google Spreadsheet template. To ensure consistency, dates were simplified to ‘MM-YYYY’ as some tools’ only had data on launch year and month, not date.
Although I did want the timeline to have a dark background (see ‘References’ section above) as my images mostly had white backgrounds, I felt that the color black could be too strong on the eyes. I searched for a slightly muted, dark tone but with a modern feel, as the subject matter is on modern technology. I used the color (#363636) obtained via a ‘Modern’ color palette post on color-hex.com as the background for all of my slides.
I initially looked for static images that represent dashboards or charts the platform can produce and that shows the brand, but found gifs to be much more illustrative of the tools’ capabilities so utilized demo gifs instead where found. As the intent of my visualization was to also provide a brief overview of the tool’s utility now, I utilized demo gifs where found to better answer that question.
Media captions were written to my best abilities to describe the image shown to make the timeline accessible for those who may not be able to take full advantage of the visualization.
After filling out and standardizing the content, I published the spreadsheet to web and generated my timeline.
The resulting Timeline created can be found via this link (also hyperlinked to the very first image of this report prior to the Introduction). Due to the lack of detail made available to the public regarding the products’ initial release notes, the actual content of the timeline only touched on each of the products superficially. However, the choices made in creating the visualization (using a standard date format, standard background color, almost standard media type, and semi-standardized text length and tone) allowed for a timeline that achieves the purpose of providing a brief yet illustrative history of modern data visualization software.
There are limitations to this visualization. First, although TimelineJS is an efficient and effective tool, the lack of flexibility around customization probably led to a less exciting and engaging timeline. The only interaction users have is clicking through the slideshow–a more engaging user-interaction such as pop-up module or hover-over actions could have been more interesting. Secondly, As the data shown were entirely based on existing articles and data visualizations, the content itself does not necessarily provide inspiring new insights into the world of visualization technology. Thirdly, although my intent was to have a standardized timeline, I was unable to find a descriptive gif for Google Charts. Hence, I had to use a static image for that slide, which takes away from the resulting work’s symmetry.
If time and resource permitted, it would be more interesting to schedule live demo-sessions with each of the companies mentioned to be able to present a better answer to my research question on the respective tool’s position and role in the world of data visualization. Another interesting research venue would be to find categories of data visualization software (e.g. timeline-creation, mapping, 3D-simulation, etc.) and using color-coding to visually cue the different buckets as demonstrated in Milestones in the history of thematic cartography, statistical graphics, and data visualization by Friendly, M. & Denis, D. J. (2001). I believe the visualization, when explored in new angles, will go from being informative for those new to the data visualization technology field to being insightful for people executing market research to purchase a product and more. My hope is that the current visualization as is provides, as the title notes, a brief overview of tools still in use today to any curious person new to understanding the current technology market in the information sciences field.
Baker, P. (2019, March 15). The Best Data Visualization Tools for 2020. Retrieved September 05, 2020, from https://www.pcmag.com/picks/the-best-data-visualization-tools
Best Data Visualization Software 2020: Reviews of the Most Popular Tools & Systems. (n.d.). Retrieved September 05, 2020, from https://www.capterra.com/data-visualization-software/
Carter, S., Andrews, W., Watkins, D., & Ward, J. (2015, January 10). The Dawn Wall: El Capitan’s Most Unwelcoming Route. Retrieved September 05, 2020, from https://www.nytimes.com/interactive/2015/01/09/sports/the-dawn-wall-el-capitan.html?_r
D. (n.d.). Modern Color Palette. Retrieved September 05, 2020, from https://www.color-hex.com/color-palette/15806 Posted by user dongkahai on the website
Friendly, M. & Denis, D. J. (2001). Milestones in the history of thematic cartography, statistical graphics, and data visualization. Web document, http://www.datavis.ca/milestones/. Accessed: September 5, 2020
Harkiran78Check out this Author’s contributed articles., Harkiran78, & Check out this Author’s contributed articles. (2020, April 06). 10 Best Data Visualization Tools in 2020. Retrieved September 05, 2020, from https://www.geeksforgeeks.org/10-best-data-visualization-tools-in-2020/
Marr, B. (2018, July 06). The 7 Best Data Visualization Tools Available Today. Retrieved September 05, 2020, from https://www.forbes.com/sites/bernardmarr/2017/07/20/the-7-best-data-visualization-tools-in-2017/
Marr, B. (2020, May 22). The 9 Best Analytics Tools For Data Visualization Available Today. Retrieved September 05, 2020, from https://www.forbes.com/sites/bernardmarr/2020/05/22/the-9-best-analytics-tools-for-data-visualization-available-today/
Wang, X. (2019, September 11). GRAPHIC REVOLUTION Timeline: AMERICAN PRINTS 1960 TO NOW. Retrieved September 05, 2020, from https://studentwork.prattsi.org/infovis/visualization/graphic-revolution-timeline-american-prints-1960-to-now/
Xie, B., He, D., Mercer, T., Wang, Y., Wu, D., Fleischmann, K., . . . Lee, M. (2020, March 13). Global health crises are also information crises: A call to action. Retrieved September 06, 2020, from https://asistdl.onlinelibrary.wiley.com/doi/full/10.1002/asi.24357