MIT Libraries

Data Management and Publishing

 

What is Data?

When we talk about data we are referring to:

  • Observational: data captured in real-time, usually irreplaceable
  • Examples: Sensor data, telemetry, survey data, sample data, neuroimages.

  • Experimental: data from lab equipment, often reproducible, but can be expensive
  • Examples: gene sequences, chromatograms, toroid magnetic field data

  • Simulation: data generated from test models where model and metadata (inputs) are more important than output data
  • Examples: climate models, economic models

  • Derived or compiled: data that is reproducible (but very expensive)
  • Examples: text and data mining, compiled database, 3D models, data gathered from public documents

Data formats can be: Storage file formats include:
Text ascii, Word, PDF
Numerical

ascii, SPSS, STATA, Excel, Access, MySQL

Multimedia jpeg, tiff, dicom, mpeg, quicktime
Models 3D, statistical
Software Java, C
Discipline specific FITS in astronomy, CIF in chemistry
Instrument specific Olympus Confocal Microscope Data Format

For advice on a data management project, contact:

data-management@mit.edu

 

MIT

For help on a data management project, contact: data-management@mit.edu

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