Definitions and Conventions

A note on conventions and definitions

In this page, you will find a one-stop guide on how to enter data according to both the conventions and definitions we follow in this wiki. They are necessary to make sure the data entered in the wiki is consistent.

• Conventions ensure data uniqueness. For instance, standardizing city entry formats prevents unnecessary duplication. Consistency in entering cities—such as using "Los Angeles" instead of variations like "Los Angeles (CA)" or "Los Angeles CA"—avoids confusion and redundancy.
• Definitions help making sure that the data is labeled according to the right category and consistently. This means:
  • Using the appropriate type of metadata. For example, a deployment's purpose cannot be "facial recognition", this is a product type. But it can be access control or border control via facial recognition.
  • Using a term that is as specific as possible. For example, some products use Fingerprint recognition, but others Finger vein recognition. If you are not sure which one to enter, you can check the difference here.

Note: All the properties are listed here in the order you will find them in the form when entering data.

Deployments

We call "Deployments" all instances in which one or more specific surveillance products (for example a smart cameras system) are deployed in a specific location, by specific institutions. Deployments can have a start and end date, can be open or closed, depending on how much is known about them.

Deployment title (page title convention)

• Our convention for deployment titles is: Product Type used by Main User in Location.
  • For example : "Face Recognition used by U.S. Customs and Border Protection - Boston Logan International Airport"

Information Certainty

• Definitions. We've organized the information we gathered into three tiers of certainty.
  • "Documented" denotes facts solidly supported by reliable sources.
  • "Rumored" encompasses information reported as potentially true but lacking confirmation.
  • Lastly, "Speculative" pertains to deployments inferred from multiple factual pieces but lacking explicit confirmation.

Deployment Status

• Definitions. While the categories are self-explanatory, we distinguish:
  • "stopped" deployments, which have been interrupted due to the intervention of a court or a watchdog for example,
  • and deployments that have naturally "concluded", either as part of an experimentation, or because they have for example been replaced with other systems.

Deployment Purpose

• Convention.
  • Chose from the existing list. If you would like to add a new purpose, please make sure it does not fit in one of the definitions below, then contact the database administrator.
  • You can add several purposes, for example Access Control, Crowd Management and Traffic Surveillance.
• Definitions. We distinguish the following purposes for which security vision systems are implemented:
  • Access Control. Systems used to authenticate individuals who can access an area (whitelist) or who are banned from it (blacklist).
  • Automated Payments. Systems using computer vision to connect to payment services.
  • Border Control. Systems used to identify travelers at the border.
  • Commercial Surveillance. Systems used to collect information and analyze customer behavior with the purpose of impacting sales.
  • Crime Prevention. Systems used to prevent or discourage criminal behavior
  • Criminal Investigations. Systems used after a crime has taken place in the context of criminal investigation (for example to identify individuals).
  • Crowd Management. Systems to gain insights on crowds and collective behaviour of people.
  • Fraud Prevention. Systems aimed at preventing fraud.
  • Fugitive Detection. Systems aimed at identifying fugitives from prisons.
  • Health Surveillance. Systems aimed at detecting diseases (through thermal monitoring) and/or the application of health measures (covid-19 mask detection for example).
  • Labor Surveillance. Systems aimed at detecting absenteeism from work.
  • Missing Person Recovery. Systems aimed at identifying missing persons.
  • Political Surveillance. Systems aimed at exercising political control over specific individuals.
  • Refugee Identification. Systems aimed at identifying refugees.
  • Student Surveillance. Systems aimed at detecting absenteeism from school or university.
  • Surveillance. Systems generally aimed at identifying and tracking individuals.
  • Targeted Advertising. A specific type of commercial surveillance, aimed at serving targeted advertisement to identified individuals.
  • Traffic Surveillance. Systems aimed at detecting traffic issues.
  • Voter & ID Registration. Systems aimed at identifying citizens or voters as part of national registries.
  • War Operations. Systems aimed at identifying individuals or other forms of control in the context of conflicts.

Timeline

• Convention
  • Please use the form to add any timeline event (start date, stop date, etc.)
  • Document it via a Zotero Citekey. If you are unsure how to generate citekeys, see the guide here.

City

• Convention.
  • Cities with unique or unambiguous names can be entered using only their name. Examples: Paris, Venice, Beijing
  • Cities in the US are always followed by their two-letter state abbreviation in parenthesis. This helps disambiguation from other cities. Examples: Los Angeles (CA), Venice (FL), Milan (MI)
    • The full list of standard abbreviations can be found here (please use the ANSI code)
  • Cities with ambiguous names outside the US should be followed by their country three-letter abbreviation, in parenthesis. Examples: Bridgetown (BRB), Georgetown (GUY).
    • The full list of standard abbreviations can be found here.

Managed by (custodian)

• Conventions
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definitions
  • The institution in charge of the maintenance of the system.

Used by

• Conventions
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.

• Definition
  • Institutions who have access to the system.

Other involved entities

• Conventions.
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definition
  • Any institution that is involved in the project, but doesn't fall in the categories of the form..

Dataset used

• Conventions.
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definition
  • The dataset used by the system.

Software used

• Conventions.
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.

• Definition
  • The specific products used by the system.

Summary

• Conventions
  • Try to limit the summary to 50-100 words, with the key information about the deployment, answering the following usual questions: who is deploying what, where and when and for what purpose.

Uncertain Information

• Refer to the uncertain entry convention

Datasets

A dataset is a structured collection and storage of data.

Dataset title (page title convention)

• Convention
  • Use the most well-known name for the dataset, preferring the abbreviation. For example: COCO or Conarc
  • When a dataset has the same name as a product, use "(Dataset)" to disambiguate . For example: Cognitec (Dataset) or CrowdOptic (Dataset)
  • When a dataset has a very widespread acronym, use the country name to disambiguate. For example ABIS (Croatia), AABIS (Afghanistan), AFIS (Italy), AFIS (Portugal)

Dataset full name

• Convention.
  • If possible, use the long name of the dataset in this property field, while the abbreviation is used for the title.

Information Certainty

• Definitions. We've organized the information we gathered into three tiers of certainty
  • "Documented" denotes facts solidly supported by reliable sources.
  • "Rumored" encompasses information reported as potentially true but lacking confirmation.
  • Lastly, "Speculative" pertains to deployments inferred from multiple factual pieces but lacking explicit confirmation.

Country

• Chose from the list

Dataset category

• Definition. Datasets are divided between datasets mainly used for:
  • Academic. Datasets used for academic research.
  • Civilian Registry. For administration purposes (identity cards, drivers licenses)
  • Law enforcement. For security purposes (registers of known criminals, refugees, etc).
  • Retail Database. Datasets used for commercial operations in retail

Developed by

• Conventions
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.

• Definition
  • The institution that has collected the information contained in the dataset and/or has made it available.

Events

• Convention
  • Please use the form to add any timeline event (start date, stop date, etc.)
  • Document it via a Zotero Citekey. If you are unsure how to generate citekeys, see the guide here.

Contents

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Specifies the type of contents available in the dataset:
  • Facial Images: images of faces
  • Fingerprints: images of fingerprints
  • Iris Scans: images of irises
  • Silhouettes: silhouettes of individuals
  • Voice: voices of individuals
• Facial images can be further specified
  • Controlled: images captured in a studio environment with a determined set of parameters for distance, light, etc.
  • Uncontrolled: images collected from a variey of different sources (social media, surveillance footage, etc.)

Owned by (Institution)

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.

• Specifies who is the owner of the dataset. Please note that it might be a different organization from the custodian, i.e. the organization in charge of maintaining and running the dataset.

Custodian (Institution)

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.

• Specifies who is the custodian of the dataset.

Funding

• Convention
  • Use the local currency when possible
• Definition
  • Information on the cost of creating and/or maintaining the dataset

Images

• Convention
  • Use only numerical values, without comas or dots. For example: 5000 or 1000000 and not 5,000 or 1 Million
• Definition
  • Number of images contained in the dataset

Individuals

• Convention
  • Use only numerical values, without comas or dots. For example: 5000 or 1000000 and not 5,000 or 1 Million

• Definition
  • Number of individuals contained in the dataset. There can be more images from the same individuals, hence the difference.

Runs database software

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new and unknown entries guidelines.
• Definition
  • The software used to operate the database

Uncertain Information

• Refer to the uncertain entry convention.

Institutions

Institution is the generic term we use to define any legal entity that is involved in security vision systems.

Institution title (page title convention)

• Convention
  • Use the most well-known name for the institution, preferring the abbreviation. For example: FBI
  • When an institution has several national operations, use the country name to disambiguate. For example 7-Eleven Australia

City (Headquarters)

• Convention.
  • Only use one city for headquarters. All other cities should be listed in branches.
  • Cities with unique or unambiguous names can be entered using only their name. Examples: Paris, Venice, Beijing
  • Cities in the US are always followed by their two-letter state abbreviation in parenthesis. This helps disambiguation from other cities. Examples: Los Angeles (CA), Venice (FL), Milan (MI)
    • The full list of standard abbreviations can be found here (please use the ANSI code)
  • Cities with ambiguous names outside the US should be followed by their country three-letter abbreviation, in parenthesis. Examples: Bridgetown (BRB), Georgetown (GUY).
    • The full list of standard abbreviations can be found here.

Address (Headquarters)

• Fill in the address of the headquarters in plain text.

City (Branches)

• Convention.
  • You can enter as many cities as necessary.
  • Cities with unique or unambiguous names can be entered using only their name. Examples: Paris, Venice, Beijing
  • Cities in the US are always followed by their two-letter state abbreviation in parenthesis. This helps disambiguation from other cities. Examples: Los Angeles (CA), Venice (FL), Milan (MI)
    • The full list of standard abbreviations can be found here (please use the ANSI code)
  • Cities with ambiguous names outside the US should be followed by their country three-letter abbreviation, in parenthesis. Examples: Bridgetown (BRB), Georgetown (GUY).
    • The full list of standard abbreviations can be found here.

Institution Type

• Convention
  • Chose from list
• Definitions
  • Company. A commercial entity engaged in business activities for profit.
  • Government. The system or group of people governing a community, state, or nation.
  • International Organization. An organization composed of multiple sovereign states or entities, established to address global issues or promote international cooperation.
  • Law Enforcement. Agencies responsible for maintaining law and order, preventing and investigating crimes, and enforcing regulations.
  • Local Government. Government institutions at the municipal level responsible for governing specific geographic areas.
  • Military. Organized armed forces typically responsible for national defense and security.
  • NGO. Non-governmental organizations are non-profit entities independent of government control, often focused on humanitarian, environmental, or social causes.
  • Regional Government. Government institutions responsible for governing specific regions within a larger political entity.
  • Research. Applied science institutions, R&D Departments.
  • School. Educational institution providing instruction and training to students (pre-university).
  • State-Local Partnership. Collaboration between state and local government entities to address common challenges or provide services efficiently.
  • University. Higher education institution offering undergraduate and postgraduate degrees in various fields of study.

Institution Sector

• Convention
  • Chose from list
• Definition. This defines the general area of operation of the institution. We define sectors as follows:
  • Academic. Universities, research centers, applied science institutions
  • Advocacy. Institutions involved in advocacy: NGOs involved in advocacy campaigns, governmental watchdogs.
  • Administration. Bureaucracies involved in the general administration of public life.
  • Art. Artistic projects or institutions
  • Education. Institutions related to the schooling system.
  • Energy. Institutions involved in the production or regulation of energy (electricity, oil, etc.)
  • Finance. Financial institutions
  • Health. Institutions involved in public health, ministries, hospitals, clinics.
  • Humanitarian. Institutions involved in providing humanitarian aid and support.
  • Retail. Institutions that sell goods and services directly to consumers for personal or household use.
  • Security. Institutions whose primary objective is the provision of security services, be them private or public. Security systems companies, law enforcement agencies, etc. They might sell security technologies, but as part of a broader involved in the security sector. For example: Thales, the Chicago Police Department.
  • Technology. Institutions primarily focused on developing software or hardware applications. While they may offer security technologies, these are typically part of a wider array of technological applications, which can span across several other sectors (health, agriculture, education, etc.). For example: Amazon, Google.
  • Telecom. Institutions involved in the provision or services in or the regulation of telecommunications.
  • Transportation. Institutions involved in the provision or services in or the regulation of transportation: Harbors, airports, etc.

URL

• Convention
  • Provide full URL (including http:// or https:// of the institution).

Related Institutions

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definition
  • Institutions related for different reasons, to specify in the bottom text.

Products

Developed by

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definition
  • The institution (company, university, ministry) that developed the product.

Technology Type

• Convention
  • Select from list
• Definition
  • ANPR. Automated Number Plate Recognition. A system to automatically read and process cars via their number plates.
  • Anomaly Detection. Identification of unusual behavior or events in data that deviate from expected patterns.
  • Audio Recognition. Identification of audio signals, commonly used for speech recognition or sound classification.
  • Control and Command Center. Centralized facility for monitoring and managing security operations, often equipped with technology for real-time decision-making.
  • Crowd Management. Automated analysis of sensor data in order to regulate the movement and behavior of large gatherings.
  • Database Software. Applications used for organizing, storing, and retrieving structured data.
  • Ear Acoustics. Identification technology based on the echo sound characteristics from the ear canal of individuals.
  • Emotion Recognition. Technologies aimed at analyzing facial expressions, gestures, or vocal cues to infer emotional states.
  • Face Mask Recognition. Identification of individuals wearing masks, used for enforcing safety protocols or security measures during public health crises.
  • Facial Recognition. Biometric technology for identifying or verifying individuals based on facial features.
  • Facial Recognition - Age Recognition. Identification of a person's age range based on facial characteristics, used for demographic analysis or age-restricted access control.
  • Facial Recognition - Authentication. Verification of a person's identity based on facial features, often used for secure access to devices or facilities.
  • Facial Recognition - Gender Recognition. Determination of a person's gender based on facial characteristics, used for demographic analysis or targeted advertising for example.
  • Facial Recognition - Live. Real-time facial recognition technology for instant identification or monitoring of individuals.
  • Facial Recognition - Retrospective. Analysis of recorded video footage to retrospectively identify individuals using facial recognition algorithms.
  • Finger Vein Recognition. Biometric method for identifying individuals based on the patterns of veins in their fingers.
  • Fingerprint Recognition. Biometric authentication technique based on the unique patterns of ridges and valleys on a person's fingertips.
  • Gunshot Detection. Automated systems for identifying and locating gunfire using acoustic sensors or analysis of audio signatures.
  • Iris Recognition. Biometric identification method based on the unique patterns in the iris of the eye.
  • Movement Recognition. Detection and analysis of human movement patterns, used for for categorizing behavior or tracking individuals.
  • Object Detection. Identification and location of objects within images or video streams.
  • Object Tracking. Monitoring the movement of objects over time within a scene.
  • Palm Print Recognition. Biometric identification technology that analyzes the unique patterns and characteristics present in an individual's palm to verify or authenticate their identity.
  • Pattern Recognition. Identification and interpretation of patterns within data, used for example in anomaly detection or image analysis.
  • People Tracking. Monitoring and tracing the movements of individuals within a given area, often used for crowd surveillance or personnel management.
  • Predictive Policing: Use of data analysis and predictive algorithms to anticipate and prevent criminal activity, aiming to determine resource allocation and crime prevention strategies.
  • Smartphone App: Mobile application software designed for smartphones.
  • Social Distancing Monitor. Device or system for enforcing social distancing measures in public spaces, often utilizing sensors or cameras to detect proximity between individuals.
  • Social Media Monitoring. Surveillance of social media platforms to gather intelligence, monitor public sentiment, or detect potential security threats.
  • Thermal Camera: Imaging device capable of detecting and visualizing heat signatures, useful for surveillance, perimeter security, and search and rescue operations.
  • Video Analysis. Automated analysis of video footage to extract relevant information, detect anomalies, or identify objects or individuals of interest.
  • Video Summarization: Condensation of lengthy video footage into shorter summaries or key highlights, facilitating review and analysis by security personnel.
  • Violence Detection. Systems for automatically identifying violent behavior or incidents within video streams, aiming to enhance public safety and emergency response.
  • Voice Recognition. Technology for identifying and interpreting spoken words or phrases, commonly used for authentication or voice-controlled systems.

Related Technologies

• Convention
  • Select from the options provided in the auto-complete suggestions.
  • You can add multiple entries.
  • If you need to add a new or unknown entry, please follow the new, unknown and uncertain entries guidelines.
• Definition
  • Other products that might be related to this one. Explain in text below.

City

is in Country

• Convention
  • Select from list
• Definition
  • The country in which the city is located

has Coordinates

• Convention
  • Copy the city name or address in the field "enter address here"
  • Press "Calculate coordinates using address"
  • The coordinates are automatically calculated, and will allow to place the city on the map in the various data visualizations.

New, Unknown and Uncertain Entries

New Entry Convention

New property

• When inside a form, you might need to add a new entry to a specific property
• Make sure the entry you want to add it is not already existing in the wiki (it should auto-complete)
• If an entry is new, after you have completed the original form, click on the red link that has been generated, and make sure to complete the appropriate form for the new entry (follow indications from this page). For example, if you add a deployment that is taking place in a city that doesn't exist in the database, you should:
  • First enter the new city in the deployment form then save the form
  • Your new entry will appear as a red link. You should then click on this link and this will lead you to create a new page (see below)

New page

• When you created a "red link" on a page, you should not leave it as such, but create the new page for the corresponding entry (for example a new city, a new company, etc.)
• Click on the red link. This will prompt you to create a new page.
  • You will have the option to create: a city, a country, a dataset, a deployment, an institution (i.e. company, ministry, NGO, etc). or a Product (a specific technology designed by a company or a state)
  • Click on the approrpriate page type and fill in the required information, according to the conventions and definitions found in this page.

Unknown Entry Convention

• In an property inside a form is unknown, you should create an unknown page.
• In order to avoid all unknown links to connect to one single "unknown page", the wiki generates automatically a new, numbered unknown entity for the property you are entering (ex. Unknown_Institution_###, Unknown_Products_###), with ### standing for a serial number.
• For institutions for example, here is the procedure to follow:
  • Click first on the "Create Unknown Institution ####" and complete the institution form in a separate browser tab, to the best of your knowledge
  • Remember the Unknown Institution #### number you've just created.
  • Once that is completed, you can close the tab and come back to the deployment form.
  • Enter the newly created unknown Unknown Institution #### with the appropriate number.
• Follow the same instructions for other Unknown categories: Unknown Dataset #### Unknown Deployment ####

Uncertain Entry Convention

• In some forms (such as Deployments) you will be given the option to add uncertain information.
• This is information about relations in the deployment.
• Select the field you want to enter from the Field dropdown.
• Enter the value of the entry
• Chose a degree of certainty
  • "Documented" denotes facts solidly supported by reliable sources.
  • "Rumored" encompasses information reported as potentially true but lacking confirmation.
  • Lastly, "Speculative" pertains to deployments inferred from multiple factual pieces but lacking explicit confirmation.
• Document the source with a Citekey. If you are not sure how to do that, check the getting started page
• Provide a description if you would like to add an additional note.