Data Sharing Policy

This policy governs the sharing of data collected through the Roadkills India citizen science campaign with researchers, conservation organisations, government bodies, and other third parties. Its purpose is to maximise the scientific and conservation value of the data while ensuring that LRCF, the Roadkills India project, and the citizen contributors receive appropriate recognition.

1. Purpose

This policy governs the sharing of data collected through the Roadkills India citizen science campaign with researchers, conservation organisations, government bodies, and other third parties. Its purpose is to maximise the scientific and conservation value of the data while ensuring that the Landscape Research and Conservation Foundation (LRCF), the Roadkills India project, and the citizen contributors who generated the data receive appropriate recognition.

2. Who Can Request Data

Data may be requested by:

• Researchers affiliated with recognised academic institutions
• Government bodies, including forest departments, highway authorities, and railway authorities
• Conservation NGOs registered in India or internationally
• Independent researchers with a demonstrable track record in wildlife science
• Students enrolled in postgraduate (master's, PhD) programmes, accompanied by a letter of support from their supervisor

Commercial entities, journalists, and individuals without a research or conservation purpose may receive only aggregated, anonymised data on a case-by-case basis at LRCF's discretion.

3. Tiers of Data Access

Data is shared in three tiers depending on the use case. Each tier has different attribution and review requirements.

Tier 1 — Aggregated Public Statistics (freely available)

Includes: total counts by state, district, year, taxon group; counts by linear infrastructure type (road / railway / power line / canal); heat maps and density estimates at coarse spatial resolution; basic descriptive statistics published by LRCF.

Available freely on the LRCF website and in LRCF's published reports. Attribution required (Section 5) but no application needed.

Tier 2 — Identified Record Data (application required)

Includes: individual record details (date, time, GPS coordinates, taxon, species, area description, infrastructure type, photo), with submitter identity removed.

Requires a written data request to LRCF (Section 4). Subject to approval. Carries attribution and reciprocal obligations (Sections 5 to 7).

Tier 3 — Citizen Contributor Information (rarely shared)

Includes: any information that can identify the citizen scientist who submitted a record (name, contact, profile photo).

Shared only with explicit consent of the individual contributor and only when scientifically necessary (e.g., re-contacting for additional details on a notable record). Personal contact data is never shared for marketing, third-party research, or commercial purposes.

Note: records submitted by users who have deleted their accounts cannot be shared in Tier 3 — once a user deletes their account, the link between user identity and records is permanently severed.

4. Data Request Process

Requests for Tier 2 data must be submitted in writing to:

The request must include:

• Name and affiliation of the requesting researcher(s)
• Research question or conservation objective
• Specific data fields requested (e.g., all mammal records, January 2024 to present, Maharashtra)
• Intended outputs (peer-reviewed publication, internal report, dissertation, etc.)
• Planned timeline
• Confirmation that all signatories agree to the terms in this policy
• For students, a supporting letter from the supervisor

LRCF will respond within 30 days. Approved requests will receive a download link or dataset file along with a Data Use Agreement to sign.

5. Attribution Requirements (Mandatory)

Any work using Roadkills India data — whether published, presented, submitted as a thesis, or used internally by a government body — must include the following attribution, prominently and in full:

5.1 Citation in publications

In the bibliography or references section:

5.2 In the Methods or Data section

The data source must be described as follows, in substance:

5.3 In the Acknowledgements

The following text must appear in the acknowledgements section of any publication, thesis, presentation, or report using Roadkills India data:

5.4 In presentations, posters, and media

LRCF and the Roadkills India project must be named on the title slide or first page, with the LRCF logo displayed at least once. For oral presentations, the speaker must verbally acknowledge LRCF and the citizen scientists.

5.5 Treatment of the data source in titles and headlines

Use of the Roadkills India dataset as the primary or sole data source must be reflected honestly. Phrasing such as "We analysed roadkill data from across India" is acceptable; "We compiled a database of roadkills across India" is not, as it misrepresents the work of LRCF and the citizen scientists.

6. Co-authorship Considerations

Co-authorship of resulting publications is not automatic, but may be appropriate where:

• LRCF staff contribute substantively to study design, analysis, or interpretation
• The dataset is the primary basis of the work (more than 70% of records used)
• Specific citizen contributors have provided substantial original observations and consent to be credited

Researchers are encouraged to discuss co-authorship with LRCF early in the project. LRCF will not assert co-authorship unreasonably but reserves the right to request it when warranted by the criteria above.

7. Reciprocal Obligations

In exchange for access to Tier 2 data, researchers agree to:

7.1 Share outputs back

A copy of any resulting publication, thesis, report, or dataset (and revised versions thereof) must be sent to LRCF within 30 days of public release or completion. LRCF maintains a public-facing list of work derived from the dataset.

7.2 No redistribution

Researchers may not redistribute the Tier 2 dataset to third parties without LRCF's written permission. This includes sharing with collaborators outside the original request, posting to repositories, or including raw data as supplementary material in publications. If raw data inclusion is required by a journal, the researcher must inform LRCF and may share only the records used in the published analysis.

7.3 No use against the contributors

Data may not be used in ways that harm wildlife, the contributing citizens, or LRCF's mission — for example, to identify and exploit poaching hotspots, to discredit the campaign, or to argue against wildlife protection measures.

7.4 Notify LRCF of corrections or updates

If a researcher identifies errors in the dataset (e.g., misidentified species, GPS errors), they must notify LRCF so corrections can be made for future users.

8. Commercial Use

The Roadkills India dataset may not be used for commercial purposes — including but not limited to selling derivative data products, training proprietary machine learning models for commercial sale, or insurance risk pricing — without a separate commercial licensing agreement with LRCF. Contact the Grievance Officer for licensing inquiries.

9. Government and Statutory Use

Data may be shared with Indian government bodies (forest departments, NHAI, railway authorities, etc.) for mitigation planning and policy purposes without the Tier 2 application process, but the attribution requirements in Section 5 still apply. LRCF retains ownership of the dataset.

10. Failure to Comply

If a researcher, institution, or organisation publishes or distributes work using Roadkills India data without complying with this policy, LRCF reserves the right to:

• Publicly issue a correction or erratum
• Contact the publishing journal or institution
• Decline future data requests from the offending party
• Pursue further action under applicable copyright and database protection laws

11. Updates to This Policy

LRCF may update this policy from time to time. The version in effect at the time of data approval governs that request.

12. Contact

For data requests, questions about this policy, or licensing inquiries: