Datendialog

Data Dialogue with CorrelAid in Berlin

On June 2 and 3, data enthusiasts from the Bertelsmann Stiftung and the nonprofit CorrelAid met for the second time at a “Data Dialogue” in Berlin. During the event, ideas were discussed for the open data portal Wegweiser Kommune (Community Roadmap) on how it would be possible to develop indicators on municipal infrastructure that go beyond official statistics.

Contact

Foto Nina Hauser
Nina Hauser
Project Manager
Foto Petra Klug
Petra Klug
Senior Project Manager

 

The Data Dialogue has existed since last year – and was initiated by the Bertelsmann Stiftung’s Data Science Lab. The idea is to collaborate with CorrelAid, a nonprofit network of data enthusiasts, to further develop our data projects by having people with different perspectives and skills come together to address a specific issue. The first dialogue focused on generating possibilities for visualizing our new population forecasts for 2040. This time, however, the goal was to look at data sources that go beyond official statistics. In addition to team members from the foundation’s Data for Society project, colleagues from the Center for Sustainable Communities and the Early Childhood Education and Care project also participated in the Data Dialogue.

Data on municipal infrastructure

Until now, our data portal Wegweiser Kommune (Community Roadmap) has primarily collected and visualized official statistics on all German municipalities with a population of 5,000 or more. At the Data Dialogue, we wanted to test whether and how we can supplement this information with useful indicators from other sources. One interesting possibility, for example, would be information on local services, which play an important role in community planning. In addition, we wanted to break new ground in terms of methodology: Can data from mapping platforms be used as the basis for calculating indicators, and what might a suitable prototype for capturing the data look like?

The pharmacy next door

We chose to start with pharmacies, one example of an important local service. Google Maps and Open Street Maps are two mapping platforms whose data can be accessed using an API. We also had data from Germany’s register of pharmacies – an important addition for checking the data’s validity. The next step was to use the country’s official community identification numbers or postal codes to locate the pharmacies within the Wegweiser Kommune geometry. Only then could we consider how to calculate indicators such as “Number of pharmacies per municipality” or “Distance of the nearest pharmacy to the town center.”

Coding phase

As the coding phase began, three teams opened their laptops: While one team optimized the data query via the Overpass API from Open Street Maps, a second simultaneously programmed the code for geographical matching using two tools: postal codes and geometric data. Another team developed indicators from the resulting datasets and checked data quality using information from the register of pharmacies. Between the sprint phases, the teams repeatedly exchanged information so they could use the work done by the others as input for their own efforts. The participants submitted their results directly via the GitHub repository they had been provided, a collaborative IT tool that the Bertelsmann Stiftung regularly uses to drive forward technological developments. The results were consolidated by our team following the Data Dialogue.

In cooperation with the data enthusiasts and the Data Science Lab, the separate functions will be brought together to create a holistic prototype that can be used to send automated data queries to mapping platforms, match geometric information with the Wegweiser Kommune portal and calculate the relevant indicators. In the future, the plan is to query other information on local infrastructure in addition to pharmacies and check the data quality using alternative data sources. Over the long term, the use of open data of this kind will make it possible for us to leverage a wealth of free information that we and others can use within a data-enrichment process to carry out insightful analyses. Working on the prototype also opened up new opportunities for exchange, including with the Thünen Institute, which is currently addressing similar data-related topics.

Are you interested in the work being done by CorrelAid? In Data4Good projects carried out in cooperation with civil society, the network of over 2,000 volunteer data scientists develops technological innovations that benefit the common good. It also trains civil society organizations and data analysts committed to helping others, thereby increasing data literacy and creating a community of data-savvy role models with civil courage.

Blog post from CorrelAid e. V.