Mapping the Datasphere
The Datasphere Initiative would like to make the “Datasphere” and its structure tangible for users and decision-makers. To do this and generate an emotional reaction to catalyze a rethinking of how the Datasphere could be collaboratively governed for the benefit of everyone, visualizations are needed to map and present the Datasphere as a whole and its different dimensions.
This project seeks to investigate paths to enable the visualization of the Datasphere as a whole and its different dimensions, building on datasets of personal and/or non-personal data in collaboration with data engineers and policy practitioners. The ultimate objective is to make the Datasphere tangible for users and decision-makers and catalyze a rethinking of how the Datasphere could be reclaimed and governed.
This is because the establishment of a baseline understanding and visualization of the nature of the Datasphere will enable well-informed decision making for practitioners.
An important requirement is that data be crowdsourced in a trustworthy and ethical manner, contrasting with exploitative means of data collection of digital footprints that too often only serve commercial purposes of large corporations.
For that reason several activities are foreseen that will range from:
Scoping and consultations with technical and policy partners and experts on Usability Scenarios, Natural Language Processing, Machine Learning, and Predictive Modeling.
Identify and catalog relevant datasets stemming from individuals or organizations, public or private.
Provide an overview of the different technological standards and norms that mint the nature of global data flows with trust.
Automate data collection for mapping and cartography the Datasphere, enabling predictive modeling on how the Datasphere will continue to expand.
Develop an interactive Datasphere Observatory platform where the Datasphere and repository of collected information can be visualized in its different layers and segments of different dataspheres.
One early example of what is possible has been undertaken in late 2021 during the incubation phase of the Datasphere Initiative in collaboration with 60 AI engineers over 8 weeks with 4 dedicated workshops to map the first dimension of the Datasphere (Human Groups, Datasets, Norms/Regulations) during a global Artificial Intelligence challenge.
It showed that rethinking how data could be governed in a more nuanced way across the data cycle of storage, transfer and processing in the future is more necessary than ever. This pilot project served as a feasibility study for the technically supported mapping of wide areas of the Datasphere across its different dimensions and is a key milestone for the development of a future Datasphere Observatory Platform.
How would the Datasphere Map look like? Discover first results of the project.
The World Map you see here shows country collaboration maps based on literature review related to data governance (Biblioshiny visualization based on Elsevier’s abstract and citation database Scopus).
The Data Governance Cluster shows the thematic evolution of data policy-related terminology mapping based on WOS (Web of Science citation database).
The Co-occurrence Network identifies patterns and relations on the data governance debate, and shows relevant concepts on the field.