examples/compliant_project/private_dataset.yaml

card_details: 
  card_type: "data" # "project", "data" or "model"
  card_label: "private_dataset"

# Metadata related to intended purpose(s) of data (which must align with those of overall AI project, if overall AI project is a high-risk AI system)

intended_purpose:
  safety_component: 
    article: 'Art. 6(1)(a)'
    verbose: 'This dataset is appropriate to use for AI projects involving product safety components'
    value: false 
  product_regulated_machinery: 
    article: 'Art. 6(1)(b); Annex I'
    verbose: 'This dataset is appropriate to use for AI projects involving products covered by Directive 2006/42/EC of the European Parliament and of the Council of 17 May 2006 on machinery, and amending Directive 95/16/EC (OJ L 157, 9.6.2006, p. 24) [as repealed by the Machinery Regulation]'
    value: false 
  product_regulated_toy: 
    article: 'Art. 6(1)(b); Annex I'
    verbose: 'This dataset is appropriate to use for AI projects involving products covered by Directive 2009/48/EC of the European Parliament and of the Council of 18 June 2009 on the safety of toys (OJ L 170, 30.6.2009, p. 1)'
    value: false 
  product_regulated_watercraft: 
    article: 'Art. 6(1)(b); Annex I'
    verbose: 'This dataset is appropriate to use for AI projects involving products covered by Directive 2013/53/EU of the European Parliament and of the Council of 20 November 2013 on recreational craft and personal watercraft and repealing Directive 94/25/EC (OJ L 354, 28.12.2013, p. 90)'
    value: false 
  biometric_categorization: 
    article: 'Art. 6(2); Annex III(1)(b)'
    verbose: 'This dataset is appropriate to use for AI projects involving biometric categorisation, according to sensitive or protected attributes or characteristics based on the inference of those attributes or characteristics'
    value: false 
  emotion_recognition: 
    article: 'Art. 6(2); Annex III(1)(c)'
    verbose: 'This dataset is appropriate to use for AI projects involving emotion recognition'
    value: true 
  critical_infrastructure: 
    article: 'Art. 6(2); Annex III(2)'
    verbose: 'This dataset is appropriate to use for AI projects involving safety components in the management and operation of critical digital infrastructure, road traffic, or in the supply of water, gas, heating or electricity'
    value: true 
  admission: 
    article: 'Art. 6(2); Annex III(3)(a)'
    verbose: 'This dataset is appropriate to use for AI projects involving the determination of access or admission or to assigning natural persons to educational and vocational training institutions at all levels'
    value: false 
  recruitment: 
    article: 'Art. 6(2); Annex III(4)(a)'
    verbose: 'This dataset is appropriate to use for AI projects involving the recruitment or selection of natural persons, in particular to place targeted job advertisements, to analyse and filter job applications, and to evaluate candidates'
    value: false 
  public_assistance: 
    article: 'Art. 6(2); Annex III(5)(a)'
    verbose: 'This dataset is appropriate to use for AI projects intended to be used by public authorities or on behalf of public authorities to evaluate the eligibility of natural persons for essential public assistance benefits and services, including healthcare services, as well as to grant, reduce, revoke, or reclaim such benefits and services'
    value: false 
  victim_assessment: 
    article: 'Art. 6(2); Annex III(6)(a)'
    verbose: 'This dataset is appropriate to use for AI projects intended to be used by or on behalf of law enforcement authorities, or by Union institutions, bodies, offices or agencies in support of law enforcement authorities or on their behalf to assess the risk of a natural person becoming the victim of criminal offences'
    value: false 
  polygraph: 
    article: 'Art. 6(2); Annex III(7)(a)'
    verbose: 'This dataset is appropriate to use for AI projects intended to be used by or on behalf of competent public authorities or by Union institutions, bodies, offices or agencies as polygraphs or similar tools'
    value: false 
  judicial: 
    article: 'Art. 6(2); Annex III(8)(a)' 
    verbose: 'This dataset is appropriate to use for AI projects intended to be used by a judicial authority or on their behalf to assist a judicial authority in researching and interpreting facts and the law and in applying the law to a concrete set of facts, or to be used in a similar way in alternative dispute resolution'
    value: false 

# Metadata related to model-related requirements when AI project is a high-risk AI system

high_risk_ai_system_requirements:
  data_and_data_governance_data_governance: 
    article: 'Art. 10(1)-(2)'
    verbose: 'The dataset was subject to data governance and management practices appropriate to the intended use case'
    value: true
  data_and_data_governance_design_choices:  
    article: 'Art. 10(2)(a)'
    verbose: 'The dataset has been subject to data governance and management practices as regards its relevant design choices'
    value: true
  data_and_data_governance_data_origin: 
    article: 'Art. 10(2)(b)'
    verbose: 'The dataset has been subject to data governance and management practices as regards its data collection processes and the origin of data, and in the case of personal data, the original purpose of the data collection'
    value: true
  data_and_data_governance_data_preparation: 
    article: 'Art. 10(2)(c)'
    verbose: 'The dataset has been subject to data governance and management practices as regards its data-preparation processing operations, such as annotation, labelling, cleaning, updating, enrichment and aggregation' 
    value: true
  data_and_data_governance_data_assumptions: 
    article: 'Art. 10(2)(d)'
    verbose: 'The dataset has been subject to data governance and management practices as regards its formulation of assumptions, in particular with respect to the information that the data are supposed to measure and represent'
    value: true
  data_and_data_governance_data_quantity: 
    article: 'Art. 10(2)(e)'
    verbose: 'The dataset has been subject to data governance and management practices that include an assessment of the availability, quantity and suitability of the data sets that are needed'
    value: true
  data_and_data_governance_ata_bias_examination: 
    article: 'Art. 10(2)(f)'
    verbose: 'The dataset has been subject to data governance and management practices that include an examination of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations' 
    value: true
  data_and_data_governance_data_and_data_governance_data_bias_mitigation: 
    article: 'Art. 10(2)(g)'
    verbose: 'The dataset has been subject to data governance and management practices that include appropriate measures to detect, prevent and mitigate possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations'
    value: true
  data_and_data_governance_data_compliance: 
    article: 'Art. 10(2)(h)'
    verbose: 'The dataset has been subject to data governance and management practices that include identification of relevant data gaps or shortcomings that prevent compliance with this Regulation, and how those gaps and shortcomings can be addressed'
    value: true 
  data_and_data_governance_data_relevance: 
    article: 'Art. 10(3); Rec. 67'
    verbose: 'Training data is relevant' 
    value: true
  data_and_data_governance_data_representativity: 
    article: 'Art. 10(3); Rec. 67'
    verbose: 'Training data is sufficiently representative'
    value: true
  data_and_data_governance_data_errors: 
    article: 'Art. 10(3); Rec. 67'
    verbose: 'Training data is, to the best extent possible, free of errors'
    value: true
  data_and_data_governance_data_completeness: 
    article: 'Art. 10(3); Rec. 67'
    verbose: 'Training data is complete in view of the intended purpose'
    value: true
  data_and_data_governance_statistical_properties: 
    article: 'Art. 10(3)'
    verbose: 'Training data possesses the appropriate statistical properties, including, where applicable, as regards the people in relation to whom it is intended to be used'
    value: true
  data_and_data_governance_contextual: 
    article: 'Art. 10(4)'
    verbose: 'Training data takes into account, to the extent required by the intended purpose, the characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting within which it is intended to be used'
    value: true
  data_and_data_governance_personal_data_necessary: 
    article: 'Art. 10(5)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the use of this data was strictly necessary'
    value: true
  data_and_data_governance_personal_data_safeguards: 
    article: 'Art. 10(5)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the use complied with appropriate safeguards for the fundamental rights and freedoms of natural persons'
    value: true
  data_and_data_governance_personal_data_gdpr: 
    article: 'Art. 10(5)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the use of this data satisfied the provisions set out in Regulations (EU) 2016/679 and (EU) 2018/1725 and Directive (EU) 2016/680'
    value: true
  data_and_data_governance_personal_data_other_options: 
    article: 'Art. 10(5)(a)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the bias detection and correction was not effectively fulfilled by processing other data, including synthetic or anonymised data'
    value: true
  data_and_data_governance_personal_data_limitations: 
    article: 'Art. 10(5)(b)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the special categories of personal data were not subject to technical limitations on the re-use of the personal data, and state-of-the-art security and privacy-preserving measures, including pseudonymisation'
    value: true
  data_and_data_governance_personal_data_controls: 
    article: 'Art. 10(5)(c)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the special categories of personal data were subject to measures to ensure that the personal data processed are secured, protected, subject to suitable safeguards, including strict controls and documentation of the access, to avoid misuse and ensure that only authorised persons have access to those personal data with appropriate confidentiality obligations'
    value: true
  data_and_data_governance_personal_data_access: 
    article: 'Art. 10(5)(d)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the special categories of personal data were not to be transmitted, transferred or otherwise accessed by other parties'
    value: true
  data_and_data_governance_personal_data_deletion: 
    article: 'Art. 10(5)(e)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the special categories of personal data were deleted once the bias was corrected or the personal data reached the end of its retention period (whichever came first)'
    value: true
  data_and_data_governance_personal_data_necessary_105f: 
    article: 'Art. 10(5)(f)'
    verbose: 'Where special categories of personal data have been used to ensure the detection and correction of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations, the records of processing activities pursuant to Regulations (EU) 2016/679 and (EU) 2018/1725 and Directive (EU) 2016/680 include the reasons why the processing of special categories of personal data was strictly necessary to detect and correct biases, and why that objective could not be achieved by processing other data'
    value: true
  technical_documentation_general_description: 
    article: 'Art. 11; Annex IV(2)(d)'
    verbose: 'Dataset carries technical documention, such as a dataseet, including a general description of the dataset.'
    value: true
  technical_documentation_provenance: 
    article: 'Art. 11; Annex IV(2)(d)'
    verbose: 'Dataset carries technical documention, such as a dataseet, including information about its provenance' 
    value: true
  technical_documentation_scope: 
    article: 'Art. 11; Annex IV(2)(d)'
    verbose: 'Dataset carries technical documention, such as a dataseet, including information about scope and main characteristics' 
    value: true
  technical_documentation_origins: 
    article: 'Art. 11; Annex IV(2)(d)' 
    verbose: 'Dataset carries technical documention, such as a dataseet, including information about how the data was obtained and selected'
    value: true
  technical_documentation_labelling: 
    article: 'Art. 11; Annex IV(2)(d)'
    verbose: 'Dataset carries technical documention, such as a dataseet, including information about labelling procedures (e.g. for supervised learning)'
    value: true
  technical_documentation_cleaning: 
    article: 'Art. 11; Annex IV(2)(d)' 
    verbose: 'Dataset carries technical documention, such as a dataseet, including information about data cleaning methodologies (e.g. outliers detection)'
    value: true
  technical_documentation_cybersecurity:  
    article: 'Art. 11; Annex IV(2)(h)'
    verbose: 'Cybersecurity measures were put in place as regards the data (e.g., scanning for data poisoning)'
    value: true  
  transparency_and_provision_of_information_to_deployers: 
    article: 'Art. 13(3)(b)(vi)'
    verbose: 'Dataset is accompanied by instructions for use that convery relevant information about it, taking into account its intended purpose'
    value: true
  quality_management_system: 
    article: 'Art. 17(1)(f)'
    verbose: 'Datset was subject to a quality management system that is documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and includes a description of the systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data'
    value: true

# Metadata related to data-related requirements when AI project is a GPAI model 

gpai_model_requirements: 
  data_type: 
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains the type of data'
    value: false
  data_provenance: 
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains the provenance of data'
    value: false 
  data_curation:
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains the curation methodologies (e.g. cleaning, filtering, etc.)'
    value: false 
  data_number: 
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains the number of data points'
    value: false 
  data_scope: 
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains the number of data scope and main characteristics'
    value: false 
  data_origin:
    article: 'Art. 53(1); Annex XI(2)(c)'
    verbose: 'Documentation for the dataset is available that contains information on how the data was obtained and selected as well as all other measures to detect the unsuitability of data sources and methods to detect identifiable biases'
    value: false