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Preserve & Share

Description

During Preserve & Share, the created and cleaned dataset is stored safely and sustainably, ensuring integrity and accessibility for the future. Furthermore, the data and documentation (and if relevant, findings) are published for external usage and availability.

Publish documentation and contextualisation on your dataset, adapting it to your intended audiences.

→ Consider your audience: For academic audiences, publish extensive documentation for the sake of understandability and reproducibility. For broader audiences, publish the extensive documentation, but include different forms of presenting results and context as well (e.g. visualisations or short summaries).
→ Use consistent formats, and publish in languages that allow for wider comprehensibility and usability. Ensure that the writing style is accessible.
→ In any version of published documentation, prioritise context and documentation necessary for harmful consequences and/or misuse of the dataset to be mitigated.
→ Highlight what cannot be found in your data, besides its value and possibilities.
→ Avoid using passive voice when describing oppressive relationships.1

Tasks

Contextualise data for external users

When undertaking this task, what should you consider?

Unintended Use

  • Can the research data be misinterpreted?
  • Or can the data be used for a different intended purpose (so-called function creep)?
  • Can any information in your dataset be viewed as misleading?

Transparency

  • If you identified gaps during the analysis process: how are you representing these to your audience?
    • For example, visualisations documentation, etc.
  • What alternative resources that may address gaps/relevant topics to your research do you refer your users to?
    • Have/Can you link this data to other archives/data?

What are good practices in relation to this task?

  • Refer and/or link to different resources that may address similar topics to your research.

  • Do not use softening language in presenting contentious pasts.2

  • Include historical and dataset creation process context, making the dataset itself, and choices made by your team clear to the users.

  • Include clear visualisations to make clear what is in your data.

    • For example: harmful language stats, category stats, uneven lengths of descriptions.

  • “Evaluate local descriptive practices and policies using the criteria: Which audiences does this description center? Which audiences does it exclude? For academic archives, this could look like making description more comprehensible for undergraduates, genealogists/family historians, and local community members. For archives collecting Spanish-language material, this could mean considering whether English-language finding aids are serving users. This could also look like minimizing archival jargon.”3

Resources

Examples of published visualisations:

Example of succinct format of showing (meta)data details:

Create or choose an interface to publish data, analyses, visualisations and other publications

When undertaking this task, what should you consider?

Accessibility

  • Who is included/excluded from data access and why?
  • Does your interface consider the digital divide?

Ownership

  • Who owns the data (legally) and is there consent for data archiving and sharing at the same time?

FAIR

  • Can your data be reused in the future?
  • Is your metadata and data open access thereby ensuring widest usability and impact?

Reproducibility

  • Is your work reproducible?

What are good practices in relation to this task?

  • Prioritise access for owners of the data and affected communities.

    • For example, Surinamese data housed in the Netherlands needs to be accessible for Surinamese citizens.4

  • Consider practical elements of accessibility.

    • For example, if your data is only accessible via a computer, this impacts the types of users you reach.

  • Ensure your published data is FAIR.

  • Offer your datasets in a format best suited to your audience or in multiple formats, such as csv and excel.

Resources

  1. Adapted from Archives for Black Lives, Anti-Racist Description Resources (2019), pp. 3-4. ↩

  2. From conversations with Historical Database of Suriname and Caribbean; Archives for Black Lives, Anti-Racist Description Resources (2019). ↩

  3. Taken from Archives for Black Lives, Anti-Racist Description Resources (2019), p. 4. ↩

  4. From conversation with Margo Groenewoud. ↩