Accessibility
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To enlarge the content, we recommend using the built-in functionality of the web browser: hold down the Ctrl key (Cmd key in OS X) and press the + or – key at the same time.
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In Windows 7, you can find a program called Magnifier if you click on the “Start” menu button at the bottom left, type Magnifier (the first few letters are enough) and press Enter. A small window will open in which everything is magnified. By default, the program tracks the position of the mouse cursor. In Windows XP, you can find Magnifier by going to Start > All Programs > Accessories > Accessibility > Magnifier.
On Apple computers, to use zoom, navigate to: Apple menu > System Preferences > Accessibility (or Universal Access) > Zoom.
Developing data management frameworks
Strong data management is the foundation of secure, reliable, and future-ready digital government. By establishing robust data management frameworks, public institutions can improve data security, ensure data quality and reusability, and enable seamless digital service delivery across sectors.
In the era of artificial intelligence (AI), effective data management is more critical than ever. eGA helps public institutions build frameworks that make data usable for advanced analytics, innovation, and AI-driven decision-making. This enables governments to deliver smarter services, improve operational efficiency, and foster data-driven policymaking.
At the e-Governance Academy (eGA), we support governments in designing and implementing comprehensive data management frameworks aligned with national priorities and international best practices. Our approach helps institutions organise, govern, and unlock the full value of public sector data while ensuring compliance, transparency, and trust.
By strengthening data governance, interoperability, and data-sharing practices, we lay the groundwork for secure, scalable, and citizen-centric digital ecosystems supporting both immediate service improvements and long-term digital transformation.
What we provide
Data Landscape Assessment: Analysing existing data systems to identify gaps, inefficiencies, and compliance risks, including those specific to AI use.
Agile Data Governance: Defining a governance model that clarifies roles, responsibilities, and decision-making processes for data and AI-driven systems.
Policy Development: Creating and updating policies for data collection, storage, access, sharing, and protection – ensuring support for secure, ethical AI applications.
Interoperability: Facilitating seamless integration between registers and digital services to ensure reliable, real-time data exchange.
Legal and Ethical Alignment: Ensuring the framework complies with evolving legal, regulatory, and ethical requirements, especially for AI governance.
Capacity Building: Strengthening digital and AI competencies among public officials to support effective data stewardship and responsible AI adoption.
