Open means different things to different people

Different interpretations of "open"—whether referring to open data, open source software, or open engagement practices—can influence a project's direction or lead to disagreements in design. For some, open tools must be intuitive and usable; for others, open means transparent, modifiable, or redistributable. Differing interpretations can cause misalignments in both design and collaboration. For example, a research project might publish data openly on an institutional repository, allowing access to community members, but it may not include contextual information or be provided in a usable format, preventing its local understanding and application. Data may be shared publicly, but remain in PDF format or embedded in poorly structured websites: these can be particularly difficult to work with, giving the appearance of transparency without enabling meaningful access, reuse, or understanding of the information.

Solutions

1.

Write a charter on openness

Explicitly define what openness means in the context of your specific research agenda or technology project. Involve different stakeholders and participants in this process. This may include creating a shared definition, or a shared understanding of how these different stakeholders are defining it in their different contexts.

2.

Articulate user personas

Develop user personas that exemplify different interests and needs around openness.

3.

Provide context for shared data

True openness requires more than accessible formats: it also needs context and structure to give the data meaning and make it usable. Explainers, descriptive information, metadata (ideally in standardized formats), visualizations, and clear or verified schema or ontologies can provide helpful context to support use beyond your original intent. Additionally, including the license under which the data can be used ensures that others understand how the data can be reused, adapted, or redistributed in different contexts.

4.

Adopt open standards

Adopt and discuss open standards for data formats, metadata, and software interoperability with your community partners. Open standards reduce barriers to entry and allow for broader discussions on what parts of a project are open and how.

Know of another resource or solution?

Resources

Values Statements

The values statements at the beginning of this toolkit offer some possible ways that different stakeholders value openness, or want to see research or technology practices apply and demonstrate openness. Likewise, working principles for collaborations can be a useful way for people to understand where asynchronous decisions-making can happen and when decisions should be brought back to the group

Related solutions
Write a charter on openness
Articulate user personas

OEDP’s Community Data Playbook

OEDP’s Community Data Playbook compiles case studies and strategies related to environmental data governance. The case studies are examples of community-based or collaborative environmental data efforts that demonstrate different needs, interests, and capacities in regards to openness. The accompanying Resource Library includes resources such as a template for creating values-oriented project ReadMes.

OEDP’s Community Data Playbook
Related solutions
Write a charter on openness
Articulate user personas

NFDI’s Ontology Collection

NFDI’s Ontology Collection is a searchable library of catalysis ontologies that can be applied or expanded depending on your research’s context. It includes several ontologies related to environmental data.

NFDI’s Ontology Collection
Related solution
Provide context for shared data

ENVO

ENVO is a community-driven ontology designed to help both humans and machines consistently describe environmental entities. It is a FAIR-compliant resource that promotes interoperability by providing controlled, concise descriptions of environmental concepts, and offers tools for annotation, browsing, and community contributions.

ENVO
Related solution
Provide context for shared data

The Semantic Sensor Network Ontology

The Semantic Sensor Network Ontology, developed by W3C and OGC, provides a standardized framework for describing sensors, their observations, related procedures, and the features or properties they monitor.

The Semantic Sensor Network Ontology
Related solution
Provide context for shared data

SPARQL

SPARQL is the query language and protocol used for retrieving and manipulating data stored in Resource Description Framework (RDF) format.

SPARQL
Related solution
Provide context for shared data

LinkML

LinkML is a general purpose modeling language that can be used with linked data, JSON, and other formats. Their cookie cutter template allows users to describe the structure of their data in a standardized way.

LinkML
Related solution
Adopt open standards

Participatory Frameworks and Tools

Participatory frameworks and tools, such as Participedia and Living Labs toolkits, offer methods for engaging with communities to achieve alignment.

Related solution
Adopt open standards