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/home/techb158/cosmic-risk.abdallabala.com/docs

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00-design-study.md	3678	0644	edit dl rm
01-uml-class-diagram.puml	11869	0644	edit dl rm
02-use-case-diagram.puml	3763	0644	edit dl rm
03-sequence-diagrams.puml	9732	0644	edit dl rm
04-database-entity-model.mmd	7051	0644	edit dl rm
05-database-schema.sql	13372	0644	edit dl rm
06-diagram-preview.html	5021	0644	edit dl rm
07-design-checklist.md	3256	0644	edit dl rm
08-step-2-storage-layer.md	5325	0644	edit dl rm
09-step-3-risk-crud-ui.md	3380	0644	edit dl rm
10-step-4-mitigation-workflow.md	3996	0644	edit dl rm
11-step-5-deployment-gate-workflow.md	2292	0644	edit dl rm
12-step-6-multi-pm-integration.md	3770	0644	edit dl rm
13-step-6-1-microsoft-planner-integration.md	2335	0644	edit dl rm
14-step-7-reporting-export.md	4158	0644	edit dl rm
15-step-7-1-oauth-live-connectors.md	4545	0644	edit dl rm
16-step-8-user-roles-access-control.md	3297	0644	edit dl rm
17-step-9-production-deployment-security.md	4228	0644	edit dl rm
18-step-10-final-academic-submission.md	3199	0644	edit dl rm
19-final-report-draft.md	6814	0644	edit dl rm
20-instructor-submission-checklist.md	3639	0644	edit dl rm
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24-evaluation-rubric-mapping.md	2910	0644	edit dl rm
25-final-deployment-runbook.md	3214	0644	edit dl rm
26-known-limitations-and-future-work.md	2632	0644	edit dl rm
27-final-qa-checklist.md	2893	0644	edit dl rm
28-demo-rehearsal-script.md	3618	0644	edit dl rm
29-submission-freeze-report.md	2769	0644	edit dl rm
30-final-known-issues.md	1876	0644	edit dl rm
31-saas-rebuild-implementation.md	2573	0644	edit dl rm
application-documentation.md	27515	0644	edit dl rm
conversation-log.md	18503	0644	edit dl rm
dashboard-spec.md	3691	0644	edit dl rm
database-guide.md	37826	0644	edit dl rm
development-summary.md	7070	0644	edit dl rm
github-architecture.svg	6288	0644	edit dl rm
integration-pull-push-plan.md	7384	0644	edit dl rm

Edit: /home/techb158/cosmic-risk.abdallabala.com/docs/26-known-limitations-and-future-work.md (2632B)

# Known Limitations and Future Work

## 1. Known limitations

| Limitation | Explanation | Suggested improvement |
|---|---|---|
| JSON storage | The prototype stores data in local JSON files | Replace with PostgreSQL, SQLite, or another database |
| Basic actor header | User identity is simulated through `X-Cosmic-User-Id` | Add full authentication with sessions or identity provider |
| Live connector credentials required | Trello, Jira, Asana, and Microsoft Planner live sync require external app registration | Complete provider-specific production setup |
| Scoring calibration | The scoring model is an implementation proposal | Validate weights with industrial case data |
| Report PDF generation | Reports are HTML and CSV, not server-generated PDF | Add server-side PDF generation if needed |
| No real-time collaboration | Updates require reload or user action | Add WebSocket or server-sent events |
| No notification workflow | Users are not notified of gate changes or overdue mitigations | Add email, Slack, Teams, or PM tool notifications |
| No advanced analytics | The dashboard focuses on operational risk tracking | Add trend analysis, forecasting, and model drift analytics |

## 2. Future work roadmap

### Phase 1: Production data layer

1. Add PostgreSQL schema.
2. Add migrations.
3. Add database indexes.
4. Add transaction-safe writes.
5. Add database backup and restore automation.

### Phase 2: Authentication

1. Add login.
2. Add secure sessions.
3. Add passwordless or SSO authentication.
4. Bind roles to authenticated users.
5. Add admin password reset workflow.

### Phase 3: Live integrations

1. Complete Trello production sync.
2. Complete Jira Cloud production sync.
3. Complete Asana production sync.
4. Complete Microsoft Planner production sync through Microsoft Graph.
5. Add retry and failure handling.
6. Add conflict resolution for bidirectional updates.

### Phase 4: Advanced governance

1. Add configurable gate policies.
2. Add organization-specific risk thresholds.
3. Add approval chains.
4. Add legal and ethical review templates.
5. Add model monitoring rules.

### Phase 5: Research validation

1. Apply the dashboard to a real AI project case.
2. Compare dashboard risk results to expert assessment.
3. Calibrate indicators and weights.
4. Document measurement validity and uncertainty.
5. Prepare academic publication or technical report.

## 3. Final note

The current system is complete enough for academic demonstration and instructor evaluation. It is not a finished enterprise product. Its main value is proving the transformation from framework to software artifact.

# Known Limitations and Future Work ## 1. Known limitations | Limitation | Explanation | Suggested improvement | |---|---|---| | JSON storage | The prototype stores data in local JSON files | Replace with PostgreSQL, SQLite, or another database | | Basic actor header | User identity is simulated through `X-Cosmic-User-Id` | Add full authentication with sessions or identity provider | | Live connector credentials required | Trello, Jira, Asana, and Microsoft Planner live sync require external app registration | Complete provider-specific production setup | | Scoring calibration | The scoring model is an implementation proposal | Validate weights with industrial case data | | Report PDF generation | Reports are HTML and CSV, not server-generated PDF | Add server-side PDF generation if needed | | No real-time collaboration | Updates require reload or user action | Add WebSocket or server-sent events | | No notification workflow | Users are not notified of gate changes or overdue mitigations | Add email, Slack, Teams, or PM tool notifications | | No advanced analytics | The dashboard focuses on operational risk tracking | Add trend analysis, forecasting, and model drift analytics | ## 2. Future work roadmap ### Phase 1: Production data layer 1. Add PostgreSQL schema. 2. Add migrations. 3. Add database indexes. 4. Add transaction-safe writes. 5. Add database backup and restore automation. ### Phase 2: Authentication 1. Add login. 2. Add secure sessions. 3. Add passwordless or SSO authentication. 4. Bind roles to authenticated users. 5. Add admin password reset workflow. ### Phase 3: Live integrations 1. Complete Trello production sync. 2. Complete Jira Cloud production sync. 3. Complete Asana production sync. 4. Complete Microsoft Planner production sync through Microsoft Graph. 5. Add retry and failure handling. 6. Add conflict resolution for bidirectional updates. ### Phase 4: Advanced governance 1. Add configurable gate policies. 2. Add organization-specific risk thresholds. 3. Add approval chains. 4. Add legal and ethical review templates. 5. Add model monitoring rules. ### Phase 5: Research validation 1. Apply the dashboard to a real AI project case. 2. Compare dashboard risk results to expert assessment. 3. Calibrate indicators and weights. 4. Document measurement validity and uncertainty. 5. Prepare academic publication or technical report. ## 3. Final note The current system is complete enough for academic demonstration and instructor evaluation. It is not a finished enterprise product. Its main value is proving the transformation from framework to software artifact.