Mapping Sexual Harassment in Public Places: Using Open-Source Data Responsibly

CASE STUDY 34 / 200

Research area: India — Delhi; spatial analysis and public-space reporting

Status: Independent desk-research draft; map findings and source data require full-paper review

Abstract / Executive Summary

Spatial mapping can help identify clusters of reported harassment and the situational features associated with incidents, but a map can also mislead when reporting access, population movement, data quality and privacy are ignored. This case study reviews a 2026 mixed-method research article mapping reported sexual harassment in Delhi. It sets out responsible principles for interpreting hotspots and translating them into prevention planning without treating open-source reports as a complete census of harm or exposing survivors.

Keywords

Delhi; spatial analysis; open-source data; harassment; hotspot mapping; privacy

1. Introduction and Research Question

How can spatial analysis of reported sexual harassment inform prevention without overstating risk or compromising privacy?

The purpose of this case study is to translate evidence into practical questions for prevention, service design and evaluation. It does not claim to investigate an individual incident or to provide a comprehensive account of all experiences.

2. Methods and Evidence Selection

Desk review of the abstract and bibliographic record for a 2026 mixed-method article on mapping sexual harassment in Delhi. The article describes spatial and descriptive analyses of reported incidents and situational factors. This report does not download, reproduce or reanalyse the original dataset, and does not claim to validate the authors’ geocoding or coding procedures.

3. Case Context

Maps can make patterns easier to communicate, but the visible distribution of reports reflects both underlying events and the process by which incidents become recorded. Areas with more people, more smartphone access, more reporting awareness or better geocoding may generate more records. Conversely, areas with limited reporting access may appear falsely quiet. Fine-grained maps can also expose people to retaliation or stigma.

4. Findings from the Reviewed Evidence

• The 2026 article describes mixed-method analysis of reported sexual-harassment incidents in Delhi, with spatial and descriptive analysis of patterns and situational factors associated with physical and non-physical harassment.
• The available abstract supports the value of contextual spatial analysis, but it does not by itself establish that the mapped reports represent all incidents or permit direct comparison of absolute risk across neighbourhoods.
• Hotspot interpretation requires denominators or exposure measures where possible, documentation of source coverage, date ranges, geocoding precision and missing-data handling.
• Public maps should avoid precise survivor locations and should distinguish verified administrative records, user-submitted reports, media-derived records and modelled estimates.

5. Discussion and Interpretation

Spatial evidence is best treated as one input to local safety assessment. Responsible publication should explain what the data include, who may be missing, how locations were generalised and whether reported clusters were validated through fieldwork. Product teams should avoid a simplistic red/green ‘safe map’ that may create false reassurance or stigmatise communities.

6. Legal and Policy Context

Privacy, data-protection, defamation, public-record access and law-enforcement data rules may apply. Obtain qualified local review before publishing incident-level information or sharing it with third parties.

7. Potential VETRIPEN Design Implications

The following are design hypotheses for research and testing, not claims that VETRIPEN currently provides these capabilities or has demonstrated effectiveness.

• Use coarse spatial aggregation and minimum-count thresholds; do not publish precise incident pins by default.
• Separate data source types and confidence levels in the interface; label unverified submissions clearly.
• Include a ‘data insufficient’ state rather than rendering an area safe when reports are absent.
• Keep user location private by default and separate emergency sharing from research analytics.
• Establish correction, deletion, abuse-reporting and moderation processes before accepting public submissions.

8. Recommendations and Evaluation Metrics

• Review the full 2026 article before using any numerical claims, maps or detailed methodological conclusions externally.
• Publish a transparent data dictionary, collection period, inclusion rules, geocoding method and known coverage gaps.
• Validate hotspot findings with participatory local audits and relevant service providers before intervention decisions.
• Audit the risk of re-identification, stereotyping and retaliation; restrict access to raw records.

Suggested metrics for future pilots: task completion under stress; consent comprehension; alert success/failure rates; false activations; accessibility task success; user-reported sense of control; trip abandonment or route change where relevant; and privacy complaints. Choose only metrics appropriate to the specific intervention and predefine how they will be measured.

9. Limitations

This report is based on the public abstract and bibliographic record rather than the complete article and underlying data. No map or hotspot is reproduced here. The report does not validate the study’s data or claim that its findings describe current risk in any specific Delhi neighbourhood.

10. Conclusion

The evidence supports a context-aware, rights-based approach that combines women’s lived experience, service accountability, physical conditions and carefully governed technology. Any proposed intervention should be tested locally, report failures honestly and avoid transferring the burden of prevention to women.

11. References and Source Notes

1. Mangai Natarajan, Eon Kim, Réka Solymosi, Dhanya Babu and co-authors (2026). Mapping Sexual Harassment in Public Places: Open-Source Data-Driven Contextual Analysis. Violence Against Women (online first; verify final bibliographic details). https://journals.sagepub.com/doi/10.1177/10778012251411830
2. Dhillon, M. & Bakaya, S. (2014). Street Harassment: A Qualitative Study of the Experiences of Young Women in Delhi. SAGE Open. https://journals.sagepub.com/doi/10.1177/2158244014543786

12. Research and Ethics Declaration

No original interviews, participant recruitment, surveys or field observations were conducted for this report. No participant quotations have been invented. Any product implications are proposals, not validated outcomes. Before external publication, verify full-text sources, bibliographic details, current laws and all numerical claims against primary materials.

Disclaimer

DISCLAIMER — INDEPENDENT RESEARCH DOCUMENT. Prepared privately by Digital Catalyzt as part of an independent research and product-design programme related to women’s safety and the proposed VETRIPEN service. For research, education, discussion and preliminary product planning only. Unless expressly stated and documented, this document has not undergone independent peer review and is not a journal publication, government statement, legal opinion, medical or psychological assessment, or formal investigation. Claims are limited to the sources and scope stated; sources may contain limitations, errors, incomplete data or later revisions. Hypothetical examples must not be represented as real events or interviews. Legal and policy discussion is general information, not legal advice. Proposed VETRIPEN features are design hypotheses unless independently evaluated. This document does not guarantee prevention of harm, emergency response, message delivery, confidentiality in every circumstance or any particular outcome. Readers should assess cited evidence, limitations and local context independently.

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