Digital responsibility refers to the ethically sensible and accountable design, operation and use of digital technologies, such as smartphone apps, IoT devices, social media, or other digital platforms. It encompasses behaviours and actions that prioritize privacy, security, accuracy, and transparency. Digital responsibility involves being aware of the potential consequences of digital actions and technologies, considering the impact on oneself and others, and making informed and ethical choices in the digital realm.
Data portability refers to the ability to transfer data from one digital platform or service to another. It allows users to move their personal data or non-personal data, such as health data, calendar entries, documents or data from IoT devices from one online service to another without losing control or ownership of their data. Data portability aims to promote user autonomy, competition, and innovation in the digital ecosystem by enabling users to easily switch between different platforms or services.
The FAIR principles are a set of guidelines for making research data Findable, Accessible, Interoperable, and Reusable. These principles were developed to promote open and transparent sharing of data in scientific and research communities, and to facilitate data-driven research and discovery. The FAIR principles provide a framework for ensuring that research data is managed in a way that maximizes its potential for reuse and reproducibility. More information: https://www.go-fair.org/fair-principles/
Data fairness refers to the equitable treatment and representation of different groups or categories of data within a dataset or data analysis process. It encompasses the idea that data should not perpetuate bias, discrimination, or unfairness towards certain groups, but rather should be collected, processed, and analysed in a manner that is unbiased, transparent, and impartial. The exchange of data should adhere to clear rules (data governance). The goal must be fair participation in the benefits achieved through the exchange of data.
Data broker / data intermediary
A data broker, also known as a data intermediary, is a business or entity that collects, aggregates, and sells or shares data collected from various sources to individual users, businesses or organizations. Data brokers act as intermediaries between data sources and data users, facilitating the exchange of data for various purposes. In the EU there are certain rules prescribing the “neutrality” of data intermediaries under the Data Governance Act
Trust by design
Trust by design refers to the intentional incorporation of trust-enhancing features and practices into the design and implementation of technologies or systems from the outset. It involves considering trust as a fundamental aspect of the design process, and ensuring that trust-related considerations are addressed proactively and systematically, rather than being an afterthought or add-on. The Digital Responsibility Goals provide a framework for achieving trust by design.
Algorithmic decision-making refers to the use of algorithms or computational methods to make decisions or predictions without human intervention. Algorithmic decision-making raises ethical, legal, and social concerns, as it can potentially perpetuate biases, discrimination, or unfairness if not properly designed, validated, or monitored. Ensuring responsibility in algorithmic decision-making is a key challenge, as it involves understanding how algorithms work, validating their accuracy and fairness, and addressing potential discriminatory outcomes.
Data sovereignty refers to the concept that individuals have the rightful ownership, control, and authority over their personal data. It asserts that individuals have the right to determine how their data is collected, used, and shared by others, and that they should have the ability to revoke or modify their consent for data processing.
AgTech & Internet of Things (IoT)
The Internet of Things (IoT) refers to the network of interconnected devices, sensors, and objects with the ability to exchange data over the internet. These devices can include a wide range of objects, from everyday items such as smartphones, wearables, and smart appliances, to industrial machinery, vehicles, and agricultural equipment. In the context of agricultural technology (AgTech), the IoT plays a crucial role in enabling smart farming practices, precision agriculture, and remote monitoring of crops, livestock, supply chains and environmental conditions, leading to increased productivity, sustainability, and resource management in agriculture.