core concepts

Question 1

Dataveillance

Answer 1

Definition: Dataveillance refers to the practice of monitoring and analysing data about individuals’ activities, behaviours, or movements, often for surveillance purposes.
Example: Monitoring internet browsing history or tracking location through GPS data for targeted advertising.
Importance: Understanding dataveillance is crucial in examining how data collection impacts privacy, autonomy, and ethical concerns in a digitally connected society.

Question 2

Proactive disclosure

Answer 2

Definition: Proactive disclosure involves the voluntary release of information or data by organizations or governments without waiting for a request.
Example: A government publishing its budget and expenditure details online for public access.
Importance: It promotes transparency, accountability, and trust between institutions and the public, fostering an informed and engaged society.

Question 3

Critical data studies

Answer 3

Definition: Critical Data Studies is an interdisciplinary field examining the social, cultural, ethical, and political implications of data collection, analysis, and use.
Example: Analyzing how algorithms in social media platforms influence user behavior and opinions.
Importance: It allows for a deeper understanding of power structures, biases, and inequalities embedded in data-driven technologies and practices.

Question 4

Volunteered geographic information

Answer 4

Definition: VGI refers to geographic data voluntarily contributed by individuals, often through platforms like mapping apps or citizen science projects.
Example: Users updating location details or adding landmarks on Google Maps.
Importance: It enriches mapping data but raises questions about accuracy, privacy, and ownership of volunteered information.

Question 5

Dematerialization

Answer 5

Definition: Dematerialization refers to the reduction or elimination of physical resources through digital alternatives, minimizing material consumption.
Example: Transitioning from paper documents to digital files.
Importance: Understanding dematerialization helps analyze environmental impacts, resource conservation, and shifts in consumption patterns in a digital society.

Question 6

Technological citizenship

Answer 6

Definition: Technological Citizenship involves the rights, responsibilities, and participation of individuals within a technological society.
Example: Engaging in online activism or advocating for digital rights.
Importance: It explores how individuals interact with technology, their rights concerning access, and participation in shaping technological developments.

Question 7

Digital twin

Answer 7

Definition: A digital twin is a virtual representation or simulation of a physical object, system, or process, often used for analysis or predictive purposes.
Example: Creating a digital replica of a manufacturing plant to optimize operations.
Importance: It facilitates better decision-making, predictive maintenance, and innovation but raises concerns about data security and privacy.

Question 8

Neo panopticon

Answer 8

Definition: Neo Panopticon refers to a contemporary system of surveillance where individuals are monitored and controlled, often through digital means, leading to self-regulation.
Example: Monitoring employee activities through computer software in a workplace.
Importance: Examining the psychological effects and power dynamics in societies influenced by constant surveillance and self-regulation.

Question 9

Surveillance creep

Answer 9

Definition: Surveillance Creep denotes the gradual expansion or normalization of surveillance practices beyond their original scope or intent.
Example: Increasing use of facial recognition technology in public spaces beyond initial security purposes.
Importance: It raises concerns about privacy infringement, erosion of civil liberties, and the need for ethical boundaries in surveillance technologies.

Question 10

Micro targeting

Answer 10

Definition: Microtargeting involves using data analysis to tailor specific messages or products to individuals or small groups based on their preferences or behaviour.
Example: Customised advertisements on social media platforms based on users’ browsing history.
Importance: It highlights the impact of personalised content on consumer behaviour, privacy concerns, and the ethical implications of targeted marketing strategies.

Question 11

open smart city

Answer 11

Definition: An Open Smart City refers to urban spaces that use open data, technology, and citizen engagement to improve efficiency, sustainability, and quality of life.
Example: Cities employing IoT devices for waste management and traffic control while making data publicly accessible.
Importance: It emphasises citizen involvement, transparency, and inclusivity in shaping the development and governance of smart cities.

Question 12

Datafication

Answer 12

Definition: Datafication is the process of transforming various aspects of life, activities, or information into data.
Example: Converting health metrics into quantifiable data for analysis using fitness trackers.
Importance: It explores how data is generated, collected, and used in diverse contexts, impacting decision-making and societal norms.

Question 13

Data feminism

Answer 13

Definition: Data Feminism examines gender biases and power structures within data collection, analysis, and interpretation, advocating for more inclusive and ethical data practices.
Example: Addressing biases in algorithms that perpetuate gender discrimination in hiring processes.
Importance: It highlights the importance of diversity, equity, and inclusion in data-related fields, challenging existing norms and biases.

Question 14

Right to repair

Answer 14

Definition: Right to Repair advocates for consumers’ rights to repair or modify their electronic devices independently, without manufacturer restrictions.
Example: Campaigns promoting access to repair manuals and spare parts for smartphones.
Importance: It raises concerns about electronic waste, consumer rights, and sustainability in a society reliant on technology.

Question 15

Quantified self

Answer 15

Definition: Quantified Self refers to individuals using technology to track and analyze personal data like fitness metrics or mood for self-improvement.
Example: Using wearable devices to monitor daily steps or sleep patterns.
Importance: It explores the implications of self-tracking on behavior, health, privacy, and self-awareness in a data-driven society.

Question 16

Data broker

Answer 16

Definition: A Data Broker is a company or entity that collects and sells consumer data to other businesses or organizations.
Example: Companies gathering and selling personal information for targeted advertising.
Importance: It raises concerns about data privacy, ownership, and transparency in the data economy.

Question 17

Data activism

Answer 17

Definition: Data Activism involves using data analysis, visualisation, or advocacy to promote social or political change.
Example: Using data visualisations to raise awareness of social inequalities.
Importance: It showcases the role of data in activism, accountability, and empowering marginalised communities.

Question 18

Dark sousveillance

Answer 18

Definition: Dark Sousveillance refers to the act of individuals or groups using covert or hidden surveillance to monitor those in positions of authority or power.
Example: Whistleblowers using hidden cameras to expose corruption.
Importance: It challenges power dynamics, enhances transparency, and holds authority figures accountable.

Question 19

Counterveillance

Answer 19

Definition: Counterveillance involves actively opposing or countering surveillance measures or systems.
Example: Using encryption tools to protect personal data from unauthorised access.
Importance: It emphasises the need for privacy protection, individual autonomy, and ethical considerations in surveillance practices.

Question 20

Open data

Answer 20

Definition: Open Data refers to data that is freely available, accessible, and can be used, reused, or redistributed by anyone.
Example: Government publishing public datasets on demographics or public services.
Importance: It encourages transparency, innovation, and collaboration while addressing issues of privacy, quality, and data governance.

Question 21

Crowdsourcing

Answer 21

Definition: Crowdsourcing involves outsourcing tasks or gathering information from a large group of people, often through online platforms.
Example: Using citizen reports to map natural disaster-affected areas.
Importance: It leverages collective intelligence, enabling diverse contributions for problem-solving and innovation.

Question 22

Augmented spatial media

Answer 22

Definition: Augmented Spatial Media combines digital information or experiences with physical spaces, enhancing perception or interaction within a physical environment.
Example: Augmented reality apps providing historical information about landmarks in real-time.
Importance: It explores the merging of physical and digital realms, impacting user experiences and societal interactions.

Question 23

Data humanitarianism

Answer 23

Definition: Data Humanitarianism involves using data analysis and technology for humanitarian purposes, such as disaster response or improving living conditions.
Example: Using satellite imagery to assess damage after natural disasters.
Importance: It demonstrates the potential of data-driven approaches in addressing humanitarian crises and societal challenges.

Question 24

Open source

Answer 24

Definition: Open Source refers to software or projects with source code accessible and available for anyone to use, modify, or distribute.
Example: Linux operating system developed collaboratively by volunteers worldwide.
Importance: It fosters innovation, collaboration, and transparency while challenging proprietary models in software development.

Question 25

Data centre

Answer 25

Definition: A Data Centre is a facility housing networked computers and storage used for data processing, management, and distribution.
Example: Large server farms storing and processing vast amounts of data for various purposes.
Importance: It underlines the infrastructure supporting digital activities and raises concerns about energy consumption and sustainability.

Question 26

Coded bias

Answer 26

Definition: Coded Bias refers to discriminatory outcomes resulting from biases within algorithms or programming code.
Example: Facial recognition systems showing higher error rates for certain demographic groups.
Importance: It highlights the need to address biases in technology, promoting fairness, equity, and accountability.

Question 27

Data walking

Answer 27

Definition: Data Walking involves exploring a physical environment while collecting data through sensors or mobile devices.
Example: Using GPS tracking to map air pollution levels while walking through a city.
Importance: It combines physical experience with data collection, fostering new perspectives on urban environments and human interactions.

Question 28

Biopower

Answer 28

Definition: Biopower refers to mechanisms of control and governance over populations through the use of biological knowledge, technologies, or practices.
Example: Policies regulating healthcare access or reproductive rights.
Importance: It examines the intersection of biology, politics, and power, impacting individual autonomy and societal structures.

Question 29

Lively data

Answer 29

Definition: Lively Data represents dynamic, interactive, or real-time data visualisations that engage users in exploring and understanding complex information.
Example: Interactive dashboards displaying live financial market data.
Importance: It enhances data comprehension and decision-making by presenting information in engaging, user-friendly formats.

Question 30

Data assemblage

Answer 30

Definition: Data Assemblage refers to the process of gathering, organizing, and connecting various data sources and elements to create a coherent representation or understanding.
Example: Combining social media data, demographic statistics, and geographic information to analyse community trends.
Importance: It emphasises the interconnectedness of diverse data sources, impacting analysis and knowledge generation.

Question 31

Dossier effect

Answer 31

Definition: Dossier Effect is the accumulation of personal or behavioral data about an individual, creating a comprehensive profile often used for surveillance or targeting.
Example: Social media platforms aggregating user data for targeted advertising.
Importance: It raises concerns about privacy invasion, profiling, and potential misuse of accumulated data.

Question 32

Crisis map

Answer 32

Definition: A Crisis Map is a real-time online map displaying information about emergencies, disasters, or crisis situations, aiding response and coordination efforts.
Example: Mapping wildfire locations and affected areas during a natural disaster.
Importance: It facilitates effective emergency response by providing timely, geospatial information to responders and affected communities.

Question 33

Citizen science

Answer 33

Definition: Citizen Science involves public participation in scientific research, enabling non-professional individuals to contribute data or observations.
Example: Birdwatchers contributing bird population data to environmental studies.
Importance: It democratises scientific research, promotes community engagement, and expands data collection capabilities across various fields.