The regional innovation ecosystem platform can display the information that is stored in it using a variety of visualisations. In that way, the user of the platform can quickly and efficiently view trends regarding the performance of the actors in the ecosystem, the main themes of their activities and the relationships between them. Each type of analysis is supported by one or more appropriate visualisations that help the user better understand the data of the platform and make inferences about the regional innovation ecosystem.
Five types of visualisations are included in the platform and are accessible from the main menu: bar charts, pie charts, scatter plots, word clouds, and node maps. Each type of visualisation is explained in more detail below.
Bar charts can be used to visualise cumulative quantitative information regarding the actors of the platform. The actors are grouped based on their type (university labs, service providers, commercial enterprises, and funding agents). The user can select the year and the quantitative variable they wish to see information about, and the visualisation is automatically updated accordingly. The variables that can be selected are:
- The number of projects that the actors were a partner in
- The number of staff working for the actors
- The amount of research grants won (for university labs) or the annual turnover (for all other actor types)
- The number of PhD students (only for university labs), and
- The number of publications published (only for university labs)
In the example above, the user has selected to see the number of projects in which the actors of the platform were involved during the year 2013. Here the user can quickly identify exact values (for example, that university labs as a whole took part in 90 projects in 2013) and also make comparisons between actor types (seeing, in this case, that commercial enterprises and university labs were the most active actor types in 2013 with respect to the number of projects they were involved in).
Pie charts show the same types of information as bar charts, but allow for even more efficient comparisons between the actor types. By hovering with the mouse over each area of the pie chart, the user can see the exact number that is represented by that area. In the example below, the user has selected to see the turnover/amount of research grants of the actors for the year 2013.
Scatter plots are able to show the same quantitative information as bar charts and pie charts, but have the advantage of displaying two variables at a time, in a two-dimensional plot. Using scatter plots, the user can identify correlations between variables for the actors in the platform. Because they represent actors as single points in the diagram, they are able to display information about each actor independently (in contrast to bar charts and pie charts that display cumulative information about each actor type). By hovering over each point, a tooltip with the name of the actor represented is displayed, along with the exact values of the two variables for that actor.
In the example above, the user chose to display the number of projects and the number of staff for the actors in the year 2012. Here, the user can get an idea about the distribution of the actors in regard to the projects undertaken and the staff they employ, and one can also identify a possible positive correlation between those two variables (i.e. that actors employing more staff tend to participate in more projects).
Word clouds show the most frequently used words in all the posts of the platform, or alternatively in posts belonging to a specific thematic area. Most frequently appearing words are shown in larger font, allowing the user to get a feeling about the main themes discussed in each thematic area, or, in other words, what the posts in that area are mostly about. The user selects the thematic area they want (or “All Thematic Areas” to select all of the thematic areas at once) and the relevant word cloud fills the rest of the page. In the example below, the user selected to see the word cloud for posts in the thematic area of “Electrical and computer engineering”. Some of the words that stand out in this area are “business”, “data” and “management”.
The node map is able to visualise the relationships between the actors of the platform, i.e. which actors have collaborated with each other in projects during one or more years. In that way, it is easy to identify groups of actors working together, as well as which actors are connected the most with others. Using checkboxes, the user can select one or more years for which to display the relevant collaborations, and can also filter the results to show collaborations involving partners in Ukraine, Belarus, or either. The node map is updated automatically after every selection and the nodes can also be dragged around with the mouse, creating a more interactive view. In the example below, the user chose to show collaborations involving either Ukrainian or Belarusian partners that took place in 2013 and 2014. In this case, one can identify eight groups of collaborators (one large group involving 11 actors, two middle-sized ones involving 6-7 actors, and five smaller ones involving 2-4 actors).