3#10 - Inga Ros Gunnarsdottir - Innovating Diversity and Inclusion in the City of Reykjavik through the role of CDO (Eng)

MetaDAMA - Data Management in the Nordics

"We believe that by making data more accessible, the city will become more transparent and accountable to the people that we serve."
In our latest MetaDAMA episode, we're joined by Inga Ros Gunnarsdottir, the Chief Data Officer (CDO) of the City of Reykjavik, who's at the forefront of a transformation towards data-driven innovation of inclusion and accessibility. She walks us through her fascinating journey from engineering at L'Oreal to shaping the future of data use in municipal services. Her insights reveal how simple text, visuals, and a focus on digital accessibility are revamping the way citizens interact with their city's data.
As we navigate the terrain of digital transformation, Inga Ros delineates the distinct roles of a Chief Data Officer versus a Chief Digital Officer, highlighting the intricacies of their contributions to a city's digital ecosystem. Reykjavik's Data Buffet serves as a prime example of how open data visualization platforms can enhance not just transparency and accountability but also literacy in a society hungry for knowledge. She also shares compelling stories of data's impact in classrooms, planting the seeds for a future where every citizen is data-literate.
We wrap up our conversation with a deep dive into the nuances of creating data visualization tools that adhere to digital accessibility standards, ensuring that everyone, regardless of ability, can partake in the wealth of information available. The discussion traverses the significance of maintaining the Icelandic language in data communication and the imperative of ethical data collection practices, especially concerning marginalized groups. By the episode's end, it's clear that the key to unlocking the full potential of data lies in the simplicity and clarity of its presentation, an ethos that Inga Ros champions and we wholeheartedly endorse. Join us on this journey to discover how Reykjavik is rewriting the narrative on data inclusivity and the profound societal transformations that follow.
My key takeaways:

• Think about how you make data available - design thinking, finding new was to visualize data is important for inclusion.
• Its the responsibility of public sector to make as much of their data openly accessible.
• The role of CDO is important, because you need someone to see the bigger picture and how data effects everyone.
• Managing data, especially for public services, comes with a social responsibility.
• The difference between a CDataO and a CDigitalO - data requires a different skill set than digital transformation.
• Data professionals need to ask the correct questions in a service design process.
• Data access and ownership should be discussed already at the design phase.
• People have expectations towards digitalization in public sector: you want to access the data you need at the time you need it, from where you are.
• «Data is a valuable societal asset, where we all have the shared responsibility to ensure data quality.»
• Data quality is a precondition for using data to its purpose and its potential.
• You need to think digital universal accessibility, when it comes to data and visualization.
• With data stories the city of Reykjavik uses visual, verbal and sound effects to convey messages through data.
• There is a focus on using accessible language, and to not over-complicate texts.
• Data, especially in the public sector, has not been collected and curated with trains AI language models in mind.
• There is a great risk that historical biases and previous lack of awareness is transmitted into our models.

Data Buffet:

• Open data visualization platform and an open data portal.
• Make as much of the city’s data easily accessible.
• Access to a wide variety of correct and reliable data is an enabler for innovation in societal services.

פרקים

1. Innovating Diversity and Inclusion (00:00:00)

2. Chief Data Officer in Digital Transformation (00:13:16)

3. Data Visualization and Language in Data Quality (00:29:23)

4. AI Language Models and Data Visualization (00:38:25)