23 Research Data Things – 1: Getting started with research data


I’m catching up on 23 (Research Data) Things from ANDS. I’m late to the party, so I’m going at my own pace and blogging my thoughts.

I found Boston University Libraries page to be very helpful, especially for identifying categories of research data:

  • Observational: data captured in real-time, usually irreplaceable. For example, sensor data, survey data, sample data, neurological images.
  • Experimental: data from lab equipment, often reproducible, but can be expensive. For example, gene sequences, chromatograms, toroid magnetic field data.
  • Simulation: data generated from test models where model and metadata are more important than output data. For example, climate models, economic models.
  • Derived or compiled: data is reproducible but expensive. For example, text and data mining, compiled database, 3D models.
  • Reference or canonical: a (static or organic) conglomeration or collection of smaller (peer-reviewed) datasets, most probably published and curated. For example, gene sequence databanks, chemical structures, or spatial data portals.

The data can be in a great amount of formats, which was quite obvious from looking around the CSIRO Data Access Portal. Having data openly available is a good start to help more people (non-scientists) access and reuse research data. Still, I don’t think many people know they can freely access actual research data like this.


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