51.1 The Replication Standard

Replicability in research ensures:

  • Credibility and comprehension of empirical studies.
  • Continuity and progression in the discipline.
  • Enhanced readership and academic citations.

For a research to be replicable, the “replication standard” is vital: it entails providing all requisite information for replication by third parties. While quantitative research can, to some extent, offer clear data, qualitative studies pose complexities due to data depth.

51.1.1 Solutions for Empirical Replication

  1. Role of Individual Authors:
    • Authors need to vouch for the replication standard for enhancing their work’s credibility.
    • Archives like the Inter-University Consortium for Political and Social Research (ICPSR) serve as depositories for replication datasets.
  2. Creation of a Replication Data Set:
    • A public data set, consisting of both original and relevant complementary data, can serve replication purposes.
  3. Professional Data Archives:
    • Organizations like ICPSR provide solutions to data storage and accessibility problems.
  4. Educational Implications:
    • Replication can be an excellent educational tool, and many programs now emphasize its importance.

51.1.2 Free Data Repositories

  1. Zenodo: Hosted by CERN, it provides a place for researchers to deposit datasets. It’s not subject-specific, so it caters to various disciplines.

  2. figshare: Allows researchers to upload, share, and cite their datasets.

  3. Dryad: Primarily for datasets associated with published articles in the biological and medical sciences.

  4. OpenICPSR: A public-facing version of the Inter-University Consortium for Political and Social Research (ICPSR) where researchers can deposit data without any cost.

  5. Harvard Dataverse: Hosted by Harvard University, this is an open-source repository software application dedicated to archiving, sharing, and citing research data.

  6. Mendeley Data: A multidisciplinary, free-to-use open access data repository where researchers can upload and share their datasets.

  7. Open Science Framework (OSF): Offers both a platform for conducting research and a place to deposit datasets.

  8. PubMed Central: Specific to life sciences, but it’s an open repository for journal articles, preprints, and datasets.

  9. Registry of Research Data Repositories (re3data): While not a repository itself, it provides a global registry of research data repositories from various academic disciplines.

  10. SocArXiv: An open archive for the social sciences.

  11. EarthArXiv: A preprints archive for earth science.

  12. Protein Data Bank (PDB): For 3D structures of large biological molecules.

  13. Gene Expression Omnibus (GEO): A public functional genomics data repository.

  14. The Language Archive (TLA): Dedicated to data on languages worldwide, especially endangered languages.

  15. B2SHARE: A platform for storing and sharing research data sets in various disciplines, especially from European research projects.

51.1.3 Exceptions to Replication

Some exceptions to the replication standard are:

  1. Confidentiality: Sometimes data, even fragmented, is too sensitive to share.
  2. Proprietary Data: Data sets owned by entities might restrict dissemination, but usually, parts of such data can still be shared.
  3. Rights of First Publication: Embargos might be set, but the essential data used in a study should be accessible.