How to use the RIS3 Innovation Maps application.

Step 1. Data Collection

a: Data Gathering
A prerequisite to the use of this application is the availability of grant data concerning innovative programmes implemented across various regions. Data sources may include regional research councils or funding providers such as the Gateway to Research (GtR) in the UK and Tekes in Finland.

Compile relevant data from these providers in the application by one or more of the following means:

  • File upload: Import a local text file. *
  • Data Import: Query stored data from the sources listed above.
  • Manual Data Entry: Design a custom format and enter or copy data into an online spreadsheet.

* Supported text formats include: ( csv, xls, ods, json etc.).

Figure 1.a.i: Data selection and upload

Additional sources may also include information exported from the RIS3 Open Data Tool (App. 5.7.). This data consists of CORDIS data concerning EU funded projects and the corresponding calls.

Figure 1.a.ii: Data selection and upload

b: Data Specification
The next step is the selection of appropriate fields and the definition of a method of classification, by business area and technology area.
At this stage it is required to specify the relevant columns containing essential information including:

  • Region
  • Funding
  • Business Area
  • Technology Classification

NOTE: It is possible to create new columns for manual data entry should this data not be available.

The OECD and NABS standards are built-in to the application and are used as standard however the user may specify a custom classification method. In order to use a custom classification two additional csv files are required to be uploaded which contain:
Column Contents Example
"chapter" Label 1.1.
"topic" Title Mathematics
"category" * Hierarchy Natural Sciences

* optional

Read more concerning classification methods here.
Note: The use of standard classifications is encouraged to allow for cross-regional and cross-country comparisons.

Figure 1b: Data import and parsing.

Step 2: Data Cleansing and Classification

Imported data will appear in the online spreadsheet where it can modified and manipulated.

Figure 2: Imported data

Classify grant data by business and technology area using the provided drop-down menus.

Figure 2: Classification of project data

Step 3: Data Visualisation, Analysis and Policy Intelligence
Visualise the data in order to analyse trends concerning regional RIS3 priorities. Build and apply filters concerning any column in order to fine-tune the analysis; E.g. filter by Region.

Figure 3a: Bubble Map Visualisation

Figure 3a: Heatmap Visualisation

Construct filters in order to refine the scope of the analysis.

Figure 3b: Filter Application

Step 4: Plotting Options and Data Export
Adjust and save the underlying data and figures.

Figure 3a: Adjusting settings and Export options

  • Modify Settings: Adjust column selection and change classification method
  • Column: Select a column in order to change the header title
  • Insert: Add a new column
  • Title: Change the plot title and file name for export
  • Format: Change the Image type for export - png, jpeg, webp or svg
  • Data: Chose to plot project count or funding
  • Scale: Adjust the bubble size for improved comparison
  • Filter: Construct filter by selecting a column and desired values

Step 5. Policy Intelligence
Analyse the data visualised by the app; for example: Identify regional strengths and concentrations of innovation activities using Heatmap plots with a regional filter or Bubble maps with classification filters. Click on the plot to find out more about a specific topic area or region.

Figure 4: Policy Intelligence