Interoperability
The capacity of diverse systems, organizations, and datasets to seamlessly exchange, interpret, and utilize data, regardless of differences in formats, structures, or standards. It is crucial in data-driven projects to enable cross-domain collaboration, unlock data value, and ensure consistent and effective communication between stakeholders.
Data management
The practice of collecting, organizing, protecting, and storing data to ensure accuracy, accessibility, and security. It covers the data lifecycle, quality control, and compliance. Effective data management improves decision-making while maintaining integrity and reducing risks.
Data governance
The framework of policies, processes, and structures that ensure data is managed and aligned with organizational goals. Governance is essential in data projects to guarantee ownership, quality, and responsible use of data.
Data risks
The potential threats and uncertainties surrounding data, including security, privacy, and ethical issues. Managing these risks is fundamental in data projects to build trust and minimize negative outcomes.
Data values
The added value generated by data in supporting decision-making, service delivery, and innovation. It highlights the strategic importance of data as a means to enhance societal and organizational impact and improve efficiency in data-driven projects.
Data openness
The degree to which data is accessible, transparent, and reusable within legal and ethical boundaries. Openness is a core value in data projects to foster innovation and generate broader societal benefits.
Data ownership
The responsibilities and rights over data, including ownership, access, and usage rights. Clarity on data ownership is crucial in data projects to ensure legal certainty and effective collaboration.