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Publish Synthesis Data Products
Data
Reproducible Research
Publish Data

Choosing to publish your data products in a long-term repository can:

  • fulfill a journal requirement to publish data
  • facilitate citing your dataset by assigning a permanent uniquely identifiable code (DOI)
  • improve discovery of and access to your dataset for others
  • enable re-use and greater visibility of your work

Data repositories vary in many ways including their specificity of topics and data types, requirements for submission, the types and formats of data they will accept, and level of curation. In general, you should (1) put your data where there are other similar types of data, and (2) include descriptive high-quality metadata that describes the dataset.

If you're looking for a data repository in which to publish your data, try searching here:

A few potential repositories to consider:

  • Knowledge Network for Biodiversity ecological and environmental research data

  • Dryad is one of several generic data repositories that is very flexible and can accept many forms of data. Dryad has a base charge $120 for hosting any dataset under 20 GB. Many journals have submission integration to coordinate reviewing and publishing manuscripts and data.

  • Environmental Data Initiative Data Portal is broadly for environmental and ecological data, including data from Long-Term Ecological Research sites. It can offer more intense data curation with more ways to browse and search for data of interest. The EDI Data Portal is also a DataONE member node.

  • Harvard Dataverse is another generic data repository that accepts individual files up to 2.5 GB and datasets up to 10 GB.

  • Qualitative Data Respository For publishing qualitative data.

More about Metadata:

Metadata is data that describes other data. It describes the contents and context of the data, and provides enough information about the data so others can understand and use your data. Domain-specific repositories sometimes require adherence to standards for metadata. Some examples of standards include:

  • Ecological Metadata Language provides a standard metadata specification for describing data relevant to the ecological discipline based on XML.

  • Darwin Core provides standardized information about biological diversity, providing reference definitions and examples.

  • Data Documentation Initiative (DDI) provides an international standard for describing data from the social, behavioral, and economic sciences in XML. Supports the entire research data life cycle.

  • Dublin Core provides a basic, domain-agnostic standard which can be easily understood and implemented. One of the most widely used metadata standards.

A few other data management resources and tools:

  • The University of Maryland Library Research Data Services provides a detailed description of data management plans, including examples.

  • GitHub repositories can be assigned DOIs through Zenodo. However, GitHub is not considered a persistent long-term archive for models and code products. You will want to find a more permanent home for your code such as one of the other repositories above. Some types of modeling communities may have specialized repositories, such as Open ABM for agent-based models.

  • Several journals specialize in data publications such as Scientific Data, and Earth System Science Data, whereas other journals have specialized article formats for this type of manuscript, such as Ecology data papers.

  • The Ecological Society of America has a list of resources and tools for data sharing here

  • The United States Geological Survey's data management guidelines

  • Oak Ridge National Laboratory's data management guidelines and best practices

  • White, E.P., Baldridge, E., Brym, Z.T., Locey, K.J., McGlinn, D.J. and Supp, S.R., 2013. Nine simple ways to make it easier to (re) use your data. Ideas in Ecology and Evolution, 6(2).

Contact us at <{{ site.email }}> if you want help finding an appropriate repository to make your data products accessible, discoverable, and citable.