When doing research, we generally divide our work into distinct stages: planning, gathering, analysing and publishing. As researchers, we are moved by curiosity to gain a deeper understanding of the world around us. We may even dream that our research can improve the lives of others. For example, clinical or field studies often seek to gain new insights on diseases or the effectiveness of new interventions.
"The goal is to transform data into knowledge and knowledge into insight."
New insight may cause us to reexamine existing conventions and challenge the status quo. Or, it may even open the door to further research. Yet how do we gain this insight? With which aim must we set out and which paths must we follow?
The Cambridge dictionary defines insight as: (the ability to have) a clear, deep, and sometimes sudden understanding of a complicated problem or situation.
To begin, we must possess the ability to gain insight. Perhaps through experience, through learning, or through research. While the former 2 are vital, we would like to focus on the later. Insight through research often requires us to aggregate data, to make sense of it and thus to obtain a unique understanding.
This data aggregation usually ends up as tabulated data, often in the form of intimidating massive spreadsheets. However, the whole is greater than the sum of its parts. Through data visualisation (the whole), these colossal spreadsheets (the parts) are refined, organised and displayed in an understandable manner. The challenge of grouping, analysing and sorting the data falls on the shoulders of the computers, while the researchers capture new insights.
What is Data Visualization?
Data visualization is the graphic representation of data (Wikipedia). It involves creating images that contextualize information and help see the relationships among the represented data. By using graphical entities like charts, graphs, and maps, data visualization tools provide a convenient way to see and understand trends in data, outliers, and even tell a story.
How to implement a Data Dashboard?
To visualize data and convert a daunting spreadsheet into descriptive graphs, you first need to choose a data visualization solution and load your data on that tool. There are two ways to do this: by either exporting and importing as CSV/Excel file or by using a REST API.
What is a REST API?
A REST API is a web service that allows computer software to exchange information with each other, using communication standards, like JSON or XML.
Using a REST API will require a certain level of technical expertise but has the benefit that once a researcher makes the connection between a data collection platform and data viz tool, that data viz tool will keep the data continuously updated.
3 data visualization tools to choose from
Power BI is a business analytics software d by Microsoft. It provides an easy-to-use interface to build interactive reports and dashboards.
Power BI Desktop is free to download https://powerbi.microsoft.com/en-us/.
Tableau is a Business Intelligence tool for visually analyzing data. Users can create and share interactive dashboards, which depict the trends, variations, and density of the data in the form of graphs, charts and maps.
Tableau offers a free version called Tableau Public: https://public.tableau.com/en-us/s/
Google's Data Studio
Data Studio is a data visualization and business intelligence solution developed by Google. Data Studio allows users to connect data from a wide variety of sources, build interactive reports and dashboards and share them with the rest of the world. Data Studio is free to use: https://datastudio.google.com/
Does Teamscope have data visualization capabilities?
Learning how to use a data visualization platform can take time and having to export data and import into a data tool visualization each time a research team wishes to visualize results can be a hassle.
Luckily Teamscope allows project teams to visualize data without leaving the platform. Teamscope supports four different chart types: pie, bar, line and basic statistical analysis. Users can build a data dashboard that is automatically updated as data is collected.
Your graphs on Teamscope can be exported any moment to various image formats like JPEG, PNG, SVG so you can customize them or use them in presentations or publications.
Our brain is drawn to perceive patterns. We can quickly distinguish colors and shapes and give them meaning. When we see a chart, our eyes are drawn to finding trends and anomalies.
Gaining insights is only possible once information is put in context.
Data visualization should accompany researchers along their entire workflow, from planning, piloting, going live and finally in the analysis phase.
It is now easier than ever to build a visually-rich dashboard. Researchers can choose from a wide array of alternatives, and in the case of Teamscope, give life to data and allow it to begin telling a story from day one.
Wikipedia contributors, "Data visualization," Wikipedia, The Free Encyclopedia, http://bit.ly/2ZuL6c0