OutcomeAtlas Specification

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OutcomeAtlas

AI Degrees, Real Outcomes.

Overview

OutcomeAtlas is an open-source, community-driven education transparency and research platform designed to document the complete financial costs, academic experiences, institutional representations, and real-world career outcomes of graduates from computer science, artificial intelligence, machine learning, data science, and related university programs.

The platform enables graduates to voluntarily submit comprehensive records of their educational expenses, including tuition, fees, housing, textbooks, equipment, scholarships, grants, and student loan obligations. By collecting detailed financial information directly from graduates, OutcomeAtlas aims to establish a comprehensive public database documenting the actual cost of obtaining technology-related degrees.

Beyond educational expenses, OutcomeAtlas examines what happens after graduation. Contributors can document employment experiences, time spent searching for work, starting salaries, career progression, underemployment, unemployment, and whether their employment opportunities align with their academic qualifications.

The platform also documents university recruitment materials, advertised career opportunities, institutional employment statistics, and representations about future technology careers. These records can be examined alongside graduate-reported experiences to identify discrepancies between institutional messaging and real-world outcomes.

OutcomeAtlas provides students, graduates, researchers, journalists, economists, policymakers, and the public with independent research tools to evaluate the relationship between higher education expenses, institutional career representations, and employment opportunities in an increasingly AI-driven economy.

Mission

To establish an independent, publicly accessible database that makes the financial costs and real-world outcomes of AI and computer science education transparent, measurable, and available for public examination.

OutcomeAtlas seeks to empower students with evidence before making significant educational investments while giving graduates a platform to document their experiences and contribute to a broader understanding of the changing technology workforce.

Core Principles

Transparency: Make educational expenses, institutional representations, and graduate outcomes accessible for independent examination.
Graduate Participation: Allow graduates to voluntarily contribute their educational and employment experiences.
Evidence-Based Research: Distinguish verified documentation, individual experiences, institutional statements, and independently sourced statistics.
Institutional Accountability: Provide tools to examine whether advertised educational and career opportunities align with reported graduate outcomes.
Data Ownership and Privacy: Protect contributor identities and sensitive financial and educational information.
Open Research: Make public aggregate datasets available to researchers, journalists, students, and policymakers.
Independence: Maintain research independence from universities, employers, technology companies, and other interested organizations.
Longitudinal Analysis: Examine educational and career outcomes over extended periods rather than relying exclusively on initial employment statistics.
Methodological Integrity: Clearly document research methodologies, reporting limitations, sample sizes, and statistical assumptions.
Human Oversight: Require human review for consequential verification, moderation, and publication decisions.

Core Modules

Graduate Registration and Identity Verification

Provide voluntary graduate registration and account management.
Support anonymous and pseudonymous public participation.
Provide optional university email verification.
Support secure degree and graduation verification.
Verify institutional attendance, degree type, academic program, and graduation dates.
Separate private identity information from publicly accessible graduate records.
Allow contributors to update, correct, or withdraw their submissions.
Provide verification status indicators.
Detect duplicate submissions while protecting contributor privacy.
Maintain transparent verification histories.
Support multiple degrees and institutions per contributor.
Provide granular consent and publication controls.

University and Educational Institution Database

Maintain a comprehensive directory of universities and colleges.
Support public, private, nonprofit, and for-profit institutions.
Record institutional names, locations, campuses, and identifiers.
Track institutional ownership and organizational changes.
Maintain historical university names, mergers, and acquisitions.
Catalog individual colleges, departments, schools, and academic divisions.
Document institutional accreditation and accreditation history.
Support domestic and international educational institutions.
Track institutional AI research initiatives and academic investments.
Maintain historical records of institutional program offerings.

Degree and Academic Program Database

Catalog undergraduate, graduate, doctoral, and professional degrees.
Support computer science, artificial intelligence, machine learning, data science, robotics, cybersecurity, software engineering, and related disciplines.
Record degree names, concentrations, and specializations.
Document program descriptions and academic requirements.
Track required and elective coursework.
Identify courses focused on artificial intelligence and automation.
Record curriculum changes over time.
Document program duration and graduation requirements.
Support online, in-person, hybrid, and distance-learning programs.
Record publicly available admission requirements.
Compare academic programs across institutions.
Track program creation, expansion, restructuring, and discontinuation.
Identify programs marketed as preparation for emerging technology careers.

Complete Educational Expense Reporting

Allow graduates to submit comprehensive educational expense records.
Record tuition costs by academic year and semester.
Include mandatory university fees and administrative charges.
Record laboratory, technology, software, and equipment fees.
Include textbooks, educational materials, and course-specific expenses.
Track housing, meal plans, transportation, and education-related living expenses.
Record computer equipment and required technology purchases.
Include internship, certification, examination, and licensing expenses.
Document scholarships, grants, fellowships, and tuition waivers.
Separate gross educational expenses from grants and scholarships.
Distinguish student-funded expenses from amounts covered by other sources.
Record federal, private, institutional, and other student loans.
Track loan interest rates, accrued interest, capitalization, and repayment obligations.
Record loan balances at graduation and subsequent repayment information.
Calculate total gross educational expenses.
Calculate net educational expenses after financial assistance.
Calculate total student-funded expenses and outstanding educational debt.
Support inflation-adjusted historical expense comparisons.
Support multiple currencies and international expense reporting.
Generate comprehensive educational cost summaries.

Career Placement and Employment Outcomes

Record employment status following graduation.
Track the time between graduation and first employment.
Document whether employment relates to the graduate’s degree.
Identify positions obtained within computer science and related disciplines.
Record employment outside the graduate’s field of study.
Document unemployment and extended job-search periods.
Track underemployment and positions below reported qualifications.
Record full-time, part-time, contract, freelance, and temporary employment.
Document internships, apprenticeships, and entry-level opportunities.
Track career changes and additional education required to obtain employment.
Record voluntarily reported job applications, interviews, and offers.
Track employment outcomes at six-month, one-year, three-year, and five-year intervals.
Distinguish employment obtained through university placement services from independent job searches.
Support voluntary employment updates throughout a graduate’s career.

Salary and Financial Recovery Analysis

Allow graduates to voluntarily report starting salaries and subsequent compensation.
Track hourly wages and annual salaries.
Record bonuses and other compensation where voluntarily disclosed.
Compare reported compensation against total educational expenses.
Calculate educational cost-to-income ratios.
Estimate educational expense recovery periods.
Compare salary outcomes across institutions and degree programs.
Track salary progression over time.
Compare graduate earnings against outstanding educational debt.
Analyze educational expenses relative to employment opportunities.
Provide regional cost-of-living adjustments.
Distinguish reported compensation from estimated and externally sourced information.
Support historical salary comparisons using inflation adjustments.

AI Industry and Workforce Disruption Intelligence

Track changes in employment opportunities across AI and computer science occupations.
Document the emergence of AI-assisted and AI-automated job functions.
Monitor changes in entry-level technology hiring.
Track AI tools that alter traditional software development responsibilities.
Identify occupations experiencing changes in required skills.
Compare historical job descriptions with current job requirements.
Document changing employer expectations for technology graduates.
Track demand for traditional programming, machine learning, AI engineering, and data science.
Identify emerging occupations and declining job categories.
Analyze relationships between AI adoption and graduate employment outcomes.
Document changes in technical qualifications and experience requirements.
Distinguish documented workforce changes from projections and speculation.

University Marketing and Career Promise Documentation

Allow graduates to submit university marketing materials and recruitment communications.
Preserve documented statements about career opportunities and employment prospects.
Collect advertised graduate salaries and employment placement statistics.
Document claims about industry demand and workforce shortages.
Record representations about the future of AI and computer science careers.
Archive publicly available program descriptions and promotional materials.
Track changes to university marketing claims over time.
Compare documented representations with voluntarily reported graduate outcomes.
Identify discrepancies between advertised and reported outcomes for further examination.
Preserve original documents, publication dates, and source information.
Distinguish institutional statements, third-party claims, and individual experiences.
Provide institutions with opportunities to submit responses and supporting documentation.

Education Return on Investment Analytics

Calculate total educational investment by graduate, degree, and institution.
Compare gross and net educational expenses.
Analyze debt-to-income ratios.
Calculate estimated educational expense recovery periods.
Compare employment rates and time-to-employment.
Evaluate degree relevance to employment.
Compare traditional computer science and AI-focused programs.
Identify programs with high costs and comparatively weak reported employment outcomes.
Analyze differences between undergraduate and graduate education.
Provide cohort-based comparisons by graduation year.
Support historical and longitudinal outcome analysis.
Identify relationships between educational costs and reported career outcomes.
Clearly distinguish descriptive statistics from causal conclusions.
Display sample sizes, reporting periods, missing data, and confidence limitations.

Employment Market and Job Listing Intelligence

Collect permitted publicly available job listing information.
Track entry-level, mid-level, and senior-level opportunities separately.
Record required degrees, certifications, and experience.
Identify positions requiring skills not typically included in university curricula.
Track employer demand for AI-related qualifications.
Compare advertised salaries with graduate-reported salaries.
Identify changes in entry-level hiring requirements.
Track geographic differences in employment opportunities.
Preserve historical job market snapshots.
Compare job availability against graduates entering the workforce.
Track changes in employer expectations for newly graduated applicants.

Institutional Accountability and Comparative Analysis

Compare universities using transparent, published metrics.
Evaluate program expenses against reported employment outcomes.
Compare institutional career placement claims with graduate submissions.
Track tuition changes relative to employment outcomes.
Identify differences between advertised and reported starting salaries.
Examine the expansion of AI-related degree programs.
Track institutional investments in AI research and academic programs.
Document partnerships between universities and technology companies.
Identify industry-sponsored programs and research initiatives.
Provide institutional response and clarification capabilities.
Maintain historical comparisons of institutional performance.
Avoid assigning misconduct or fraud labels without independently established evidence.

Evidence Collection and Document Management

Accept supporting documentation from graduates.
Support tuition statements, financial aid records, loan statements, and transcripts.
Accept employment offers, rejection communications, and job application records.
Support university advertisements and recruitment materials.
Preserve original submission dates and document metadata.
Generate document hashes to detect subsequent alterations.
Support document authenticity checks.
Redact personally identifiable information before public publication.
Maintain source attribution and document provenance.
Distinguish verified documents from unverified statements.
Allow authorized reviewers to examine supporting evidence.
Maintain histories of document corrections and verification decisions.

Data Verification and Quality Assurance

Implement structured submission validation.
Identify incomplete financial records.
Detect duplicate submissions.
Flag conflicting educational and employment information.
Identify anomalous expense reports for additional review.
Calculate consistency between reported totals and individual expense entries.
Support independent verification of institutional information.
Establish confidence indicators for individual records.
Maintain verification status at the field and submission levels.
Provide transparent methodology for aggregate statistics.
Allow community members to report suspected inaccuracies.
Preserve corrections without silently rewriting historical records.

Public Research and Data Analytics

Provide searchable graduate outcome datasets.
Enable filtering by university, degree, specialization, and graduation year.
Compare individual programs and institutions.
Generate regional and national educational cost comparisons.
Analyze employment trends across graduation cohorts.
Examine relationships between AI adoption and employment outcomes.
Identify differences between traditional computer science and AI-focused education.
Support longitudinal research.
Provide downloadable aggregate datasets.
Publish reproducible research methodologies.
Support independent academic research.
Provide statistical summaries with sample sizes and limitations.
Allow researchers to build custom comparative analyses.
Clearly distinguish correlation from causation.

Interactive Data Visualization

Provide interactive university comparison dashboards.
Display average and median educational expenses.
Visualize total student debt.
Compare employment and unemployment rates.
Display time-to-employment distributions.
Visualize reported salary distributions.
Compare degree costs against employment outcomes.
Display geographic distributions of graduates.
Map institutional locations and graduate destinations.
Compare historical graduation cohorts.
Visualize AI-related employment changes.
Display program-level and institution-level trends.
Allow users to customize charts and comparison criteria.
Provide downloadable charts and research summaries.

Graduate Experience and Testimonial Management

Allow graduates to share their educational experiences.
Support anonymous written testimonials.
Document expectations before enrollment.
Record experiences during academic study.
Document post-graduation job searches.
Capture differences between expected and actual career opportunities.
Record additional education or retraining required.
Allow graduates to describe the usefulness of their coursework.
Document perceived gaps between academic preparation and employer requirements.
Separate personal experiences from independently verified facts.
Allow contributors to update or remove public testimonials.
Provide mechanisms for reporting abusive or inappropriate submissions.

Student Decision Support

Allow prospective students to research institutions before enrollment.
Compare total program expenses across universities.
Examine reported employment outcomes for specific degrees.
Review graduate salary distributions.
Compare student debt and career outcomes.
Explore historical outcomes by graduation year.
Examine program curricula against employer requirements.
Identify additional certifications or training reported by graduates.
Provide questions students should ask university admissions departments.
Allow prospective students to build hypothetical educational cost estimates.
Provide transparent explanations of reporting limitations.
Support customized university and degree comparisons.

Public Transparency and Institutional Response

Provide public university and program profiles.
Publish aggregate graduate submissions.
Display research methodologies and verification standards.
Allow universities to submit factual corrections.
Provide institutional responses to published research.
Preserve the distinction between university statements and graduate experiences.
Maintain auditable histories of changes to public records.
Provide a right-of-reply process.
Publish correction and dispute histories.
Prevent institutions from unilaterally removing legitimate graduate submissions.
Maintain editorial independence from universities and technology companies.

Supporting Platform Modules

Contributor Privacy and Data Protection

Provide privacy-first registration and submission workflows.
Minimize collection of personally identifiable information.
Separate identity verification from public graduate profiles.
Encrypt sensitive information in transit and at rest.
Provide granular consent controls.
Allow contributors to determine which information becomes public.
Provide secure document storage.
Establish data retention and deletion policies.
Protect contributors against unauthorized access.
Prevent public exposure of private financial documents.
Support privacy-preserving aggregate reporting.
Provide clear disclosures regarding data usage.

Community Moderation and Governance

Establish transparent community participation guidelines.
Support volunteer moderators and designated reviewers.
Provide submission review queues.
Allow community members to flag inaccurate information.
Establish an appeals process.
Publish moderation policies.
Maintain records of moderation actions.
Prevent harassment and targeted abuse.
Establish conflict-of-interest disclosures.
Prevent universities, employers, and outside organizations from manipulating aggregate results.
Support independent oversight and community governance.

Open Data and Public API

Provide a documented public API.
Allow researchers to query publicly available datasets.
Support structured data exports.
Provide CSV, JSON, and other interoperable formats.
Publish standardized institutional identifiers.
Provide consistent degree and occupation classifications.
Support bulk aggregate dataset downloads.
Provide API access for academic researchers and journalists.
Support integration with independent research platforms.
Publish database schemas and data dictionaries.
Maintain versioned datasets.
Document changes to data definitions and calculation methodologies.

Search and Discovery

Search universities, colleges, and academic programs.
Search degree names and specializations.
Find graduate submissions by graduation year and program.
Filter by tuition, student debt, and reported salary.
Search employment outcomes and occupational categories.
Discover institutions offering AI-related degrees.
Compare similar programs across different regions.
Support advanced multi-criteria searches.
Provide saved searches and comparison lists.

Reporting and Research Publications

Generate university-specific reports.
Generate degree-specific reports.
Generate regional and national reports.
Produce graduation cohort analyses.
Generate educational expense reports.
Produce employment outcome comparisons.
Publish AI workforce impact research.
Support downloadable research summaries.
Provide citations and source references.
Maintain publication histories.
Allow independent researchers to contribute studies.
Support peer review and methodology feedback.

Notifications and Contributor Engagement

Notify contributors when new research is published about their institution or program.
Allow contributors to receive updates on their degree category.
Notify users when submissions require additional verification.
Provide reminders for optional graduate outcome updates.
Notify contributors when corrections or disputes affect their records.
Support subscriptions to university and program updates.
Provide project announcements and community updates.

Administration and Platform Management

Provide role-based administrative permissions.
Manage universities and academic programs.
Review and verify submissions.
Manage document verification.
Handle contributor disputes.
Manage public reports and research publications.
Monitor data integrity.
Manage API access and usage.
Maintain administrative audit logs.
Provide platform activity statistics.
Support multiple independent platform administrators.
Maintain transparent governance and operational policies.

Accessibility and Internationalization

Support accessible interfaces and navigation.
Follow WCAG accessibility guidelines.
Support screen readers and keyboard navigation.
Provide mobile-friendly experiences.
Support multiple languages.
Support international currencies.
Account for differences in educational systems.
Support international degree classifications.
Allow comparisons across countries while accounting for reporting differences.
Support regional education expense and employment classifications.

Optional Plugin Modules

Optional plugins extend OutcomeAtlas with specialized capabilities without requiring changes to the core modules. Each plugin should be independently installable, configurable, and removable while maintaining compatibility with the platform’s core data standards.

AI Research Assistant

Summarize public graduate outcome data.
Identify patterns in educational expenses.
Analyze changes in employment requirements.
Generate research questions.
Assist with comparisons between degree programs.
Summarize publicly available university marketing materials.
Identify potential inconsistencies for human review.
Generate draft research reports with supporting citations.
Clearly identify AI-generated analysis.
Require human review before publishing research conclusions.

AI Curriculum Analysis

Analyze publicly available university course descriptions.
Compare course content with current AI industry requirements.
Identify potentially outdated course material.
Compare traditional computer science curricula with AI-focused curricula.
Identify missing or underrepresented subject areas.
Track curriculum changes over time.
Compare academic learning objectives with reported employer requirements.

University Marketing Intelligence

Monitor publicly available university program pages.
Archive changes to program descriptions.
Track advertised career outcomes.
Compare historical recruitment messaging.
Track changes in AI-related program marketing.
Generate historical comparisons of institutional representations.
Preserve source URLs, publication dates, and archived evidence.

External Employment Data Integration

Connect to public employment datasets.
Integrate government labor statistics.
Import publicly available occupational projections.
Connect to permitted job listing data sources.
Compare graduate-reported outcomes against external employment statistics.
Document source, collection date, and licensing restrictions.
Support multiple employment data providers.

Economic and Workforce Intelligence

Integrate inflation and consumer price data.
Compare historical educational expenses.
Analyze regional salary differences.
Compare education expenses against broader economic conditions.
Track occupational growth and contraction.
Analyze changes in technology industry hiring.
Compare historical and current workforce demand.

Independent Research Workspaces

Allow researchers to create private analytical workspaces.
Build custom datasets from public records.
Create reusable research queries.
Develop comparative university studies.
Publish reproducible research notebooks.
Share research findings with the community.
Support collaborative academic research.

University Response Portal

Provide institutions with designated response accounts.
Allow universities to submit factual corrections.
Accept documentation supporting institutional responses.
Allow institutions to publish explanations of program changes.
Maintain independent editorial review.
Preserve historical responses and corrections.
Provide transparent institutional response histories.

Graduate Career Tracking

Allow graduates to periodically update employment information.
Track career progression.
Record salary changes.
Document career transitions.
Measure long-term degree relevance.
Track additional certifications and education.
Compare graduate outcomes over extended periods.
Support optional longitudinal participation.

Future Development

OutcomeAtlas should remain modular and extensible, allowing additional academic disciplines, institutional categories, employment classifications, research methodologies, and data integrations to be introduced over time.

Future development should prioritize comprehensive graduate participation, accurate educational expense reporting, longitudinal employment tracking, independent verification, transparent research, and accessible public data.

The platform should support independent deployments and allow communities, research organizations, and educational transparency initiatives to operate their own instances while maintaining interoperable data standards.

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system.
Copyleft enforced for network deployments.
Required attribution:
- Roxanne Ardary
- https://www.roxanneardary.com/

Optional

Specification Branding License (SBL)
- Attribution-free commercial deployment.
- Pricing based on scale, usage, and deployment scope.
- https://roxanneardary.com/outcomeatlas/

License & Notice Requirements

OutcomeAtlas is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

By contributing to any Open Arsenal project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to: Roxanne Ardary and roxanneardary.com.
OutcomeAtlas specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – OutcomeAtlas

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – November 4, 2026
Created the repository for OutcomeAtlas. Developed the project concept, specifications, and feature framework for an open-source education transparency and research platform documenting the complete costs of AI and computer science degrees, graduate employment outcomes, student debt, and institutional career representations.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – OutcomeAtlas

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points:

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.