BASIC INFORMATION

► Name name (required)
What is the colloquial name used to identify this use of the algorithm?
Examples: 'WMO prediction Rotterdam', 'Crowd-monitoring Enschede', 'Top 400/ 600'

type: string

► Responsible organization organization (required)
What is the official name of the organization responsible for the use of the algorithm?
Examples: 'City of Amsterdam', 'Water Authority Limburg'

type: string

► Department department (required)
What is the name of the department, division, programme, team, ... using the algorithm?
Examples: 'District Segbroek', 'Traffic and transport', 'Public safety'

type: string

► Geographical area area (required)
Official name of the geographical area in which the algorithm is being used.

type: string

► Domain domain (required)
In which domain will the algorithm be deployed?
Examples: justice, finance, 'travel, living and working abroad'

type: enum

► Short summary description_short (required)
Please give a short summary of maximum 150 chars in order to give a quick overview of the purpose of the algorithm.
Examples: 'The traffic light priority algorithm prioritises traffic modalities based on applicable law and local regulations'

type: string

► Website website
URL of a human readable web page for this registration, for example on the organization web page or public algorithm register.
Examples: https://algoritmeregister.amsterdam.nl/vroeg-eropaf/

type: url

► Risk category risk_category (required)
Classification of the risk category for this use of the algorithm. Check for more information: https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital-age/excellence-trust-artificial-intelligence_en.

type: enum

► Status status (required)
Status of the use of algorithm.

type: enum

► Remark remark
Add a remark to this registration.
Examples: This project was ended because of ...

type: string

USE CASE

► Decision-making process decision_making_process
What is the formal process in the organisation in which the algorithm will be/is involved?
Examples: refer to concrete laws, regulation or policy, as published in publicly available sources

type: string

► Goals goal
What are the goals of the policy for which the algorithm is being/was put in place and how will the application expectedly contribute to reaching these goals?

type: string

► Impact impact
In what way will people come into contact with the effects of the algorithm. Under what specific circumstances will this happen and what are the expected consequences on the individual level and/or societal level?

type: string

► Risks risks
Please indicate which risk assessment was used and give an overview of the risks and mitigation measures.
Examples: risk assessments such as the audit framework 'understanding algorithms' by the Netherlands Court of Audit, and the regulation on a European approach for artificial intelligence

type: string

► Proportionality proportionality
Explain why use of the algorithm is reasonably necessary. Explain why the expected benefits outweigh any potential expected harm.

type: string

► Lawful basis lawful_basis
Which administrative act makes the use of the algorithm legitimate?

type: string

► More information documentation
URL reference to any extended information about the use of the algorithm 0within this specific use case.

type: url

DATA

► Source data source_data
Please give an overview of the data that is being processed by the algorithm. It should describe the pupose with which each data source is added and possible dependencies that result from this.

type: string

► Training data training_data
Please give an overview of the data that was used for training the algorithm. It should describe the pupose with which each data source was added.

type: string

► Data bias data_bias
Does the source data contain a certain bias? How is this compensated for?

type: string

► Description of the DPIA DPIA_description
Please give an overview of the key points from the data protection impact assessment. It should explain how discrimination is prevented when (proxies of) ethnicity, sex or zipcode are being used.

type: string

► DPIA URL DPIA_url
URL to the full DPIA documentation.

type: url

ALGORITHM

► Explanation description
Please provide an extensive description between 500 and 10000 chars explaining the inner workings of the algorithm. It should detail all relevant aspects that are needed to understand how the algorithm processes data and feeds decision making.

type: string

► Type of algorithm type
Please indicate wether the algorithm is descriptive, diagnostic, predictive or prescriptive. This information can be used as a possible risk indicator.

type: enum

► Methods and models methods_and_models
Please indicate which known methods or models the algorithm is using.
Examples: ROC-curve, confusion matrix, expert system, neural network

type: string

► Considered alternatives alternatives_considered
Were there any other options considered? Why is this algorithm the best fit for the given goal?

type: string

► Central registration URL publiccode_url
URL for the central public information on this algorithmic application or publiccode.yml file.

type: url

► Source code URL application_url
URL reference to the code base of the algorithmic application.
Examples: link to a Github repository, the Common Ground Component Catalogue, supplier website.

type: url

► Landing page URL landing_url
URL reference of the landing page/product page with further information about the algorithmic application? This facilitates users searching more in-depth information about the practical use or technical details.

type: url

► Connections to data sources MPRD
Please indicate wether a connection is being made to the Municipal Personal Records Database and specify other relevant connections.

type: string

► Algorithm impact assessment AIA_description
Please indicate which algorithm impact assessment was used and give an overview of the key points.
Examples: impact assessments such as FRAIA, AIIA, capAI

type: string

► Algorithm impact assessment URL AIA_url
URL to the full AIA documentation.

type: url

OVERSIGHT

► Performance monitoring performance
Please describe what the expected performance of the algorithm is and how this monitored.
Examples: which criteria are used, how frequently is the performance monitored

type: string

► Human intervention human_intervention
Please describe how the outcomes of the algorithm can be intervened with by humans. It should detail how the responsibility for possible human intervention is secured, so it's clear who can and may act.

type: string

► Objection procedure objection_procedure
Please describe in what way can people object against the use or outcome of the algorithm.

type: string

► Rollback rollback
Is it possible to roll back the effects of the algorithm? What does that take?

type: string

METADATA

► Version of the standard used standard_version (required)
Version of the standard used for this registration.

type: const

► Unique identifier uuid
Universally unique identifier for this registration.

type: uuid

► Contact person name contact_name (required)
Name of the contact person for this registration.

type: string

► Contact person e-mail contact_email (required)
E-mail address of the contact person for this registration.

type: email

► Contact person phone number contact_phone (required)
Phone number of the contact person for this registration.

type: string

► Language lang (required)
ISO 639-1 for the language in which this registration was filled in.
Examples: 'en', 'nl'

type: string

► Revision date revision_date (required)
Date before which this registration has to be revisited.

type: date

► Revision date note revision_note
Why is the revision planned?
Examples: start of pilot, end of pilot, yearly

type: string

► Last change date last_change_date (required)
Date of the last change to this registration.

type: date

► Keywords keywords
Keywords that might help finding this information.

type: string