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Open Data, Open Science

Reproducibility, data ethics, and contributing to the scientific commons

Grades UG 90 min research live IESH data

Undergraduate students examine the principles of open science and data ethics, evaluate the HICS dataset against FAIR principles, design a data governance framework for community-owned environmental data in Nepal, and contribute quality-controlled readings to the himalayansciences.org platform.

Learning objectives

  • Articulate the FAIR data principles and evaluate a dataset against them.
  • Identify ethical issues in environmental data collection, including consent, benefit-sharing and data sovereignty.
  • Design a basic data governance framework appropriate for a community-owned sensor network in Nepal.
  • Contribute quality-controlled data to an open repository with appropriate metadata.

Background

The open science movement argues that scientific knowledge — methods, data, software and publications — should be freely accessible to all, not locked behind journal paywalls or proprietary databases. The FAIR principles (Findable, Accessible, Interoperable, Reusable) are a practical framework for implementing open data. Findable means the data has a persistent identifier (like a DOI) and rich metadata. Accessible means it can be downloaded freely. Interoperable means it uses standard formats and vocabularies. Reusable means it has a clear license and sufficient documentation to be understood by others.

Data ethics asks harder questions. Who consented to data being collected? Who benefits from the data — the community whose environment is monitored, or the researchers who publish it? Who has the right to delete data, correct errors, or restrict access? In the context of community-owned environmental monitoring, these questions are not theoretical. A sensor installed in a village without the community's knowledge and understanding violates principles of informed consent and local data sovereignty, even if the data itself is scientifically valuable.

Data sovereignty is the principle that communities have the right to govern data about their own territories and environments. For Nepal's indigenous communities in particular, this matters: data about their land, resources and climate has historically been collected by outsiders for outsiders' purposes. A genuinely community-owned sensor network changes this — but only if communities understand, control and benefit from the data it generates.

Procedure

  1. Access the HICS dashboard /api/data endpoint. Examine the JSON response. Evaluate it against each FAIR principle: is the data Findable, Accessible, Interoperable, Reusable? Score 1–4 for each.
  2. Identify THREE specific improvements to the API response or documentation that would increase the FAIR score.
  3. Case study: a foreign university installs 10 soil sensors across a farming village in Humla. They collect 2 years of data, publish a paper, and then the project ends. The sensors are removed and the data is kept on the university's server. Identify three ethical problems with this scenario.
  4. Design a data governance framework for a community-owned sensor network. Include: who controls access, how data is licensed, how the community benefits, what happens when the project ends.
  5. Export or record a set of quality-controlled readings with full metadata (station location, altitude, sensor model, calibration status). Write a 200-word data description following scientific repository standards.
  6. If API access is configured: submit one week of quality-controlled data to himalayansciences.org. Document the submission process.

Discussion

  1. Can environmental data be "owned"? If a community's rainfall is measured, who owns that measurement?
  2. Open data is presented as democratising knowledge — but who actually benefits most from freely available environmental data? Is this distribution equitable?
  3. Nepal's government holds climate and environmental data that could be used to validate community sensor readings. What would it take to make this data publicly accessible?

Worksheet

1. Evaluate the HICS sensor API against each FAIR principle. Give a score out of 4 for each and justify your score with one specific observation. [8 marks]

Answer guide (for teachers)

F: likely 2–3 (data accessible at known URL but no persistent DOI, limited discovery metadata). A: 3–4 (freely accessible over local network). I: 2–3 (JSON is standard but no controlled vocabulary, no linked data). R: 2 (no explicit license, limited documentation). Award marks for quality of justification.

2. Define "data sovereignty" and explain why it is particularly relevant to indigenous communities and environmental monitoring in Nepal. [5 marks]

Answer guide (for teachers)

Data sovereignty: the right of a community to govern data collected about their territory or people. Relevant to Nepal because indigenous communities have historically had data about their land and resources collected by outsiders for outsiders' benefit, without consent or benefit-sharing. Environmental sensor data about a community's field, water or air is information about their livelihood and territory.

Vocabulary

FAIR Principles
A framework for scientific data management: data should be Findable, Accessible, Interoperable and Reusable.
Data Sovereignty
The right of communities or nations to govern and control data collected about their people, land and resources.
Open License
A legal mechanism (e.g. Creative Commons) that grants others the right to use, adapt and redistribute data or content.
Persistent Identifier
A long-term reference (such as a DOI) that identifies a digital resource and remains valid even if the resource moves.

Extension

Draft a one-page "Community Data Agreement" for a fictional village in Nepal that agrees to host an IESH sensor station. The agreement should cover: who owns the data, who can access it, how the community benefits, what happens to the data and equipment if the project ends, and how disputes are resolved. Have it reviewed by a law or development studies lecturer if possible.

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