Government Remote Work Compliance Tracker

This dataset provides granular, up-to-date tracking of government department staff compliance with remote work policies, including eligibility, digital access, training, and readiness for digital transformation. It enables policy makers, HR teams, and smart city planners to identify gaps, optimize digital operations, and benchmark progress across distributed public sector workforces.

  • last updated 27 Oct 2025
  • by GoMask
The brief that made it

Monitoring and reporting remote work compliance across government departments

Sample rows

preview · 8 of 34 rows · all 21 columns
record_idstringpolicy_versionstringdigital_transformation_readinessfloatremote_work_eligiblebooleandepartment_idstringdepartment_namestringemployee_idstringemployee_namestringjob_titlestringpolicy_effective_datedateremote_work_statusstringlast_remote_work_check_datedatenon_compliance_reasonstringdigital_access_scorefloattraining_completedbooleanlocation_citystringlocation_statestringlocation_countrystringremarksstringrecord_created_atdatetimerecord_updated_atdatetime
REC-0001RW-2023.287.2trueDPT-101Department of TransportationEMP-001-101Maria RodriguezProject Manager2023-05-01compliant2024-05-28blank92.3trueSan FranciscoCaliforniaUSAFully compliant. High digital literacy.2024-05-28T09:15:212024-05-29T08:30:09
REC-0002RW-2024.178.4trueDPT-102Ministry of HealthEMP-002-102James LeeData Analyst2024-01-10non-compliant2024-05-29Incomplete training84.6falseSeattleWashingtonUSATraining scheduled for next month.2024-05-29T10:18:002024-05-29T11:02:55
REC-0003RW-2023.181.9trueDPT-103Department of EducationEMP-003-103Li WeiIT Specialist2023-03-15pending2024-05-27blank91falseBostonMassachusettsUSAPending training completion.2024-05-27T08:40:452024-05-27T09:11:23
REC-0004RW-2023.275.3trueDPT-104Dept. of Environmental AffairsEMP-004-104John SmithEnvironmental Engineer2023-11-01compliant2024-05-25blank88.8trueHoustonTexasUSAblank2024-05-25T15:25:302024-05-25T17:43:10
REC-0005RW-2023.287.2falseDPT-101Department of TransportationEMP-005-101Olga PetrovaLogistics Coordinator2023-05-01exempt2024-05-26blank67.2falseSacramentoCaliforniaUSARole requires on-site presence.2024-05-26T10:03:142024-05-26T11:14:32
REC-0006RW-2024.190.1trueDPT-105Ministry of FinanceEMP-006-105Amit KumarCompliance Officer2024-01-10compliant2024-05-28blank95.5trueChicagoIllinoisUSADigital access exceeds benchmarks.2024-05-28T11:46:502024-05-29T08:04:11
REC-0007RW-2023.180.7trueDPT-106Department of Public SafetyEMP-007-106Grace JohnsonHR Coordinator2023-03-15pending2024-05-29blank78.1falseBaltimoreMarylandUSAAwaiting training module update.2024-05-29T13:54:382024-05-29T14:32:12
REC-0008RW-2024.193.6trueDPT-107Ministry of Urban DevelopmentEMP-008-107Samuel KimGIS Analyst2024-01-10compliant2024-05-27blank98.1truePhoenixArizonaUSAExcellent digital infrastructure.2024-05-27T09:10:222024-05-28T09:17:43

What the 34 rows show

from the 34-row sample

RW-2024.1 (policy version) stands out: mean digital_transformation_readiness is 90.3, against 80.8 for the rest.

  • 79%remote_work_eligible = true
  • 81.9median digital_transformation_readiness
  • 4remote work statuses
  • 7department names
  • 83.7median digital_access_score
Mean digital_transformation_readiness by policy_version34 rows
05010080.4RW-2023.214 rows90.3RW-2024.110 rows81.3RW-2023.110 rows
digital_transformation_readiness34 rows, in bands of 2
051050510005054748494digital_transformation_readiness →

Median 81.9, from 75.3 to 93.6.

department_id34 rows · 7 values
  1. DPT-1015
  2. DPT-1025
  3. DPT-1035
  4. DPT-1045
  5. DPT-1055
  6. DPT-1065
  7. DPT-1074
21 columns by typefrom the column list below
  • string 13
  • float 2
  • date 2
  • datetime 2
  • boolean 2

Columns

21 columns in four groups
blueprint · 21 columns
columntypedescriptionexample
Text 13 columns
record_idstringUnique identifier for each compliance recorduniqueREC-0001
department_idstringUnique identifier for the government department7 departmentsDPT-101
department_namestringFull name of the government department7 namesMinistry of Health
employee_idstringUnique identifier for the employeeEMP-001-101
employee_namestringFull name of the employeeMaria Rodriguez
job_titlestringEmployee's job title or positionProject Manager
policy_versionstringVersion or identifier of the remote work policy in effect3 versionsRW-2023.2
remote_work_statusstringCurrent remote work status of the employeecompliant · non-compliant · pending · exemptcompliant
non_compliance_reasonstringReason for non-compliance if applicableoptionalIncomplete training
location_citystringCity where the employee is basedSan Francisco
location_statestringState or region where the employee is basedCalifornia
location_countrystringCountry where the employee is basedUSA
remarksstringAdditional notes or comments regarding compliance or digital readinessoptionalDevice upgrade required.
Numbers 2 columns
digital_access_scorefloatScore (0-100) indicating employee's access to required digital tools and infrastructure0 to 10092.3
digital_transformation_readinessfloatScore (0-100) indicating department's overall readiness for digital transformation0 to 10087.2
Dates and times 4 columns
policy_effective_datedateDate when the remote work policy became effective2023-05-01
last_remote_work_check_datedateDate of the most recent compliance check for remote work2024-05-28
record_created_atdatetimeTimestamp when the record was created2024-05-28T09:15:21
record_updated_atdatetimeTimestamp when the record was last updated2024-05-29T08:30:09
True or false 2 columns
remote_work_eligiblebooleanIndicates if the employee is eligible for remote work under current policytrue
training_completedbooleanIndicates if the employee has completed remote work trainingtrue

Use it for

  • remote work el…79%27 of 34 rowsmean digital transfor…80.4RW-202…90.3RW-202…81.3RW-202…

    A government dashboard

    The remote_work_eligible rate, digital_transformation_readiness by policy_version and a breakdown of department_id. Excel, Power BI or Tableau.

  • Why do the 10 RW-2024.1 rows have a mean digital_transformation_readiness of 90.3?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable records with department_id, department_name and employee_id to fill a screen in front of a buyer.

Not quite right?

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This dataset34 rows21 columns
Yours1,000 rows21 columnslocation_city: UK only

blueprint · government-remote-work-compliance-tracker

Behind this dataset

Same schema. As many rows as you need.

These 34 rows came out of a blueprint — 21 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a department's weekly compliance summary.
  • Includes % of staff meeting remote work protocols.
  • Flags non-compliance incidents and reasons.
  • Tracks digital tool usage per department.
  • Departments must have at least 20 staff.
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
government-remote-work-compliance-tracker

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