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Research data

    Main points

What a researcher considers to be 'research data' depends on the meaning of this data in the research process. This varies for each scientific discipline. 

Research data comes in a variety of formats that can be read with various types of software. The accordion below shows a few definitions of research data.  

Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media.(1)

Research data is defined as recorded factual material commonly retained by and accepted in the scientific community as necessary to validate research findings.(2)

Research data: Collected, observed or created for the purpose of analysis to produce and validate original research results.(3)

Research data is the material underpinning a research assertion.(4)

University of Southampton staff have drafted a document(5) in which they have defined five different ways to look at research data: 

  • The way the data is collected.
    • By experimenting, simulations, observations, derived data, reference data.
  • The data forms.
    • For example text documents, spreadsheets, lab journals, logs, questionnaires, software code, transcripts, code books, audio and video recordings, photos, samples, slides, artefacts, models, scripts, databases, metadata, etc.
  • The formats for electronic storage of the research data.
  • The size (volume) of the data files.
  • The research lifecycle phase the data is in.

   Practise

This exercise is from the RDM Rose activity sheet 5.2.2. It is an optional exercise that can be done to get a better understanding of the term research data.   

Case studies

On page 6-22 of Scott et al. (2016) you will find five case studies about research data in the following fields: 

  1. medical research
  2. materials science
  3. aerodynamics
  4. chemistry
  5. archaeology

Select one case study to examine in detail and answer the following two questions:

  • Do you recognize the five ways to look at research data? How?
  • Identify a number of possible issues researchers have (or could have) when they want to store, manage, archive and share their research data. 

Feel free to post your findings on the forum.

  Sources and additional reading

  Your additions 

Do you want to comment on this section? Or add another definition of research data or complementary source? Please let us know by posting a comment. 


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Frans de Liagre Böhl - Inhet artikel van Scott et al. worden vijf manieren om naar research data te kijken onderscheiden. De twee manier is gekenschetst door de ´form of research´. Ter verduidelijking wordt een aantal vormen van research opgevoerd. Ik krijg de indruk dat deze opsomming gemankeerd is; ´spreadsheet´ of ´Laboratory notebooks, field notebooks and diaries´ schijnen mij geen vormen van onderzoek, hooguit manieren om de resultaten van een vorm van onderzoek vast te leggen. Zie ik wat over het hoofd?

11 months 4 days ago · 
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S Bohle - E-science has been more broadly interpreted since then, as "the application of computer technology to the undertaking of modern scientific investigation, including the preparation, experimentation, data collection, results dissemination, and long-term storage and accessibility of all materials generated through the scientific process. These may include data modeling and analysis, electronic/digitized laboratory notebooks, raw and fitted data sets, manuscript production and draft versions, pre-prints, and print and/or electronic publications." https://en.wikipedia.org/wiki/E-Science (Bohle, S. "What is E-science and How Should it Be Managed?" Nature.com, Spektrum der Wissenschaft (Scientific American), http://www.scilogs.com/scientific_and_medical_libraries/what-is-e-science-and-how-should-it-be-managed/.)

8 months 3 weeks ago · 
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Erik Jansen - In het artikel van Scott et al. wordt voor backups verwezen naar enkele non-free alternatieven waaronder Dropbox. Wat niet vermeldt wordt is dat je niet weet op welke server in de wereld je data worden opgeslagen. In welke gevallen is dit iets om rekening mee te houden?

7 months 1 week ago · 
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Research Data Netherlands - @Erik: het stellen van de vraag is het suggereren van een antwoord... Als het, al is het "maar" om het principe, noodzakelijk of wenselijk is dat je data onder Nederlandse of Europese jurisdictie vallen, is Dropbox af te raden. Voor veel Nederlandse onderzoekers is SURFdrive een goed en soms ook verplicht alternatief.

7 months 1 week ago · 
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Rob Oosterling - De link naar Scott geeft een error: EPrints System Error
Error connecting to database: Can't connect to local MySQL server through socket '/var/lib/mysql/mysql.sock' (111)

2 months 1 week ago · 
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Rahul Thorat - I am very familiar with experiment conducted in section materials science. The research data is gathered by conducting experiment on a square rod with a crack to measure the fatigue resistance of the material (when and how the material will fail, given the repeated stress cycle). This is an example of indirect experimental data because you cannot measure the property (fatigue resistance) directly. The computer measures signals from the voltmeter, the potential difference (strain in the material) caused by the material as a reaction to applied stress cycles (N), hence da/dN.

Storage of data: The strain in the material is interpreted as potential difference. The potential difference from the instrument is converted, with a signal processor, into tangible format like a csv file with columns, (time, signal (mV)).
Manage the data: Mere signal does not mean anything. The conversion of signal (mV) into the strain in the materials (usually distance unit, micrometer in this respect) is necessary. Most of the signal processor comes with a standard procedure of conversion. Further the instrument needs calibration, without which, it is hard to convince anybody that you have a legitimate data. The standards are the best practice within given industry of signal processing for such experiment. Pay attention!! the standards can vary from material to material!
Archive the data: Once the conversion of the signals is done in the csv management program like Excel, it becomes easier to observe, clean, plot and draw data for conclusions. The archiving can also be done by saving the worksheet as a csv file.
Share the data: Anybody with program for managing csv file (Excel, origin, Matlab environment, R enviornment) can use the data. However it becomes very important to have metadata of the experiment : why you did the experiment, which material, the instruments used, naming of the columns etc.

1 month 1 week ago · 
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