This document sets out the guiding principles for how CaSTCo partners should govern their data and associated data management systems to ensure the greatest benefit and value for all stakeholders and contributors.
How to cite: CaSTCo (2024). Data Governance Principles for Collaborative Monitoring.
[https://castco.org/data-governance/]
These principles are continually informed and adapted based on learning from ongoing initiatives, including drawing upon national and international best practices such as the FAIR (Findable, Accessible, Interoperable, Reusable) principles for scientific data management and the EU Data Governance Act (DGA).
1. Open by default
Data should be openly available with minimal restrictions to promote reuse for wider purposes, transparency, collaboration, and innovation.
Making data open involves minimising or removing barriers to data access and use, such as restrictive data sharing agreements or the use of proprietary data formats that require specialist or costly software. For many organisations and groups, making the decision to share their data openly for others to freely use, modify or re-share without any restrictions or controls is considered high risk. However, we can minimise these risks and maximise the benefits of sharing data openly by ensuring the necessary legal and technical processes are followed, for example, publishing data with a licence.
What CaSTCo is working towards…
- Data is open and free at the point of use by default
- Data is only restricted to protect personal or sensitive information
- Data is published with clear and appropriate data licenses to avoid misuse and disputes
- All data can be downloaded in a non-proprietary, structured, machine-readable format, or accessed via an API / web service
- Data is provided with sufficient metadata at the point of access to make it usable and/or assess fitness for use in any given context
- Where possible, openly publish source code for any software or tools developed
2. FAIR (findable, accessible, interoperable, reusable)
Removing technical and administrative obstacles to finding, sharing and using data.
There is an urgent need to improve the infrastructure supporting the discovery and reuse of environmental monitoring data, which relies upon both technological and human elements. From a technological standpoint, we need to create systems that support the cooperative flow and integration of data (including metadata) from different sources across platforms, ideally using automated processes for efficiency and to reduce the barrier to entry for non-technical users. Human elements include consistent communication and engagement among stakeholders and users to agree on standardised approaches and inform the development of systems, as well as remaining highly flexible to allow the system to adapt to the evolving needs of end users and rapid development of technological solutions.
What CaSTCo is working towards…
- Implementation of metadata standards
- Adoption of data standards for measurements and observations
- Data published in open formats (non-proprietary, structured, machine-readable) and comprehendible to users
- Data can be or is integrated with other data platforms using APIs (Application Programming Interfaces) or web services
- Data is published in a timely manner to support reuse and decision-making
3. Trustworthy
Data is of known quality, and there is transparency in the methods and standards followed, any validation processes, and potential biases.
Even when data is shared openly, it can often be overlooked or omitted by decision-makers due to a lack of clarity around data quality. Processes should be put in place to ensure that data is as accurate and reliable as possible. Monitoring and assessment, including citizen science, will continue to cover a range of approaches, from higher accuracy but less extensive to very widely used but lower accuracy measurements. It is therefore important that factors impacting data quality, such as the sensitivity of equipment, level of training given to surveyors, etc., are made transparent and embedded in metadata, and made available to users of the data.
What CaSTCo is working towards…
- Quality assurance and quality control procedures integrated in standardised methods and protocols
- Data is cleaned before publication to reduce the processing burden on end users
- Better understanding the accuracy and quality of standardised methods and protocols
- A tiered framework to categorise data quality and appropriate end uses
- Embedding data quality indicators in metadata
4. Secure
Common privacy and security standards are followed to safeguard data against corruption or loss.
Cybersecurity is a critical and rapidly evolving issue that cannot be ignored, and all organisations that are responsible for storing and managing data should ensure that best practice is followed to protect their repositories from corruption or loss over time. This is especially true for sensitive data that may be subject to legal regulations, such as personal data under the General Data Protection Regulations (GDPR) or endangered species data under the Wildlife and Countryside Act or Conservation of Habitats and Species Regulations.
What CaSTCo is working towards…
- Awareness of and improved compliance with existing laws and relevant regulatory guidance
- Clear guidance for organisations, their staff and volunteers, on data privacy and data rights and obligations
- Rigorous and transparent measures in place to safeguard sensitive information from the public for the protection of people and the environment
5. User-centred
User needs are prioritised to promote inclusivity, minimise barriers to access and incentivise participation.
Systems, data and associated resources must be designed with a primary focus on meeting the evolving needs and expectations of stakeholders and end users. This must include efforts to motivate and empower individuals, irrespective of their technical abilities, to collaborate around shared data and information.
What CaSTCo is working towards…
- Ongoing feedback mechanisms to ensure that systems and services remain aligned with user needs
- Recognising and rewarding data sharing and technological contributions to incentivise future collaboration
6. Ethical
Ethical considerations are addressed in data collection and usage, taking steps to mitigate biases and promote fairness.
Data can hold significant power and influence when published in the public domain. In some cases, it is imperative that data is protected or presented appropriately for ethical reasons. For example, where it could lead to unlawful persecution of an individual or business or result in poor decision-making. It is important that individuals and organisations responsible for the collection and sharing of data have considered any consequences that could result in harmful or undesirable outcomes and take reasonable steps to mitigate against them.
What CaSTCo is working towards…
- Respecting cultural, environmental, and human rights considerations in data collection and sharing processes
- Awareness of any potential undesirable side effects from releasing data
- Assessing the sensitivity of different types of data and outlining suitable guidance, procedures and measures to mitigate against bias, misuse or privacy violations
7. Resilient
Consider the long-term sustainability and scalability of data systems and ensure long-term preservation of data stored within them.
Regular maintenance and updates are essential to keep systems running smoothly, securely and effectively over time, as well as keeping pace with rapidly evolving technologies and shifting user-needs. This requires careful planning and sufficient resources in both the short and long-term. It is also important to have data preservation plans in place to make sure that valuable data is not lost or destroyed and remains accessible in the future even if a project or initiative ends, software is no longer available, or unexpected challenges arise.
What CaSTCo is working towards…
- Systems designed to be flexible and adaptable to meet current and future needs
- Securing sufficient long-term funding and resources to ensure continuity of service for critical apps and systems
- Legacy plans in place to ensure that valuable data is not destroyed and remains accessible, even if the initiative or project is no longer operational
Glossary
| API | A software interface that enables the programmatic (coded) exchange of information between software applications using requests and responses |
| Interoperability | The ability of computer systems or software to exchange and make use of data and information |
| Metadata | Data that provides context or additional information about data |
| Non-proprietary software | Available in the public domain (open source) or widely licensed |