Prepare your research data for deposit

Before depositing data and related documentation with the research data archive at Sikt, we recommend that you review these checklists for depositing quantitative or qualitative data.

If you prepare your data by using these checklists, the depositing process will be easier, and you will receive less feedback after the quality control of the data. 

Depositing quantitative data

All digital formats can be deposited, but SPSS/.sav files are recommended. If you transfer data in excel or csv, we encourage you to keep numeric values in the cells and provide a codebook with explanation of the values. 

Give the data file(s) a name that is self-explanatory.

1: Control all variable names. 

  • We recommend that variable names in the data file match variable names in a codebook, question names in a questionnaire, or variable references in other documentation sources. 
  • Variable names should not exceed 32 characters. This is because longer variable names will be cut during data conversion to some data formats. 

2: Add self-explanatory variable labels to all variables. 

  • All variables in the data file must have a label. The label should be short and concise. 

3: Add value labels to all response categories in discrete/categorical variables.

  • Code values should have explanatory text so that it is easy to understand what the values represent. 
  • Missing values: If you have numerical values that represent invalid responses, these should be defined as missing. 

4: Remove all unnecessary variables from the dataset, such as: 

  • Empty variables 
  • Dummy variables 
  • Duplicate variables 
  • Constructed analysis variables: 
  • If you want to keep these variablesin the data file for replication purposes, we strongly recommend that the construction procedure is well described. 

5: Review the frequency tables of the variables and control that they look reasonable.

  • Include codebooks and/or questionnaires so that variable names can be linked to correct documentation. 
  • Include documentation reports and other documents related to the dataset. (Articles, book chapters, or books related to the data material (PDF document or persistent link/DOI)). 
  • Fill out the archiving form so that as much information as possible about the method, sample, collection period, etc. for the dataset is documented. 
  • Look at text variables with open-ended responses, do they contain any person-identifying information? 
  • Look at background variables, can person-identifying information emerge indirectly from the compilation of these? 
  • Remove or recode any variables that may possibly identify individuals in the dataset. 
  • After receiving your data deposit, we will control the dataset for anonymity and can provide suggestions for anonymization if necessary. Please feel free to contact us if you have any questions concerning anonymization. 
  • Include documentation that the dataset can be archived and shared with indirect/direct person-identifying information. 
  • Example: An information letter, a consent form, or documentation from Sikt’s Data Protection Services, the Norwegian Data Protection Authority, or the Regional Committees for Medical and Health Research Ethics (REK).

A data processing agreement must also be in place between the research institution and Sikt if the dataset contains personal data.

The data processing agreement should include information about: 

  • The data that is to be archived. 
  • How long the data will be stored. 
  • The purpose of archiving the data.
  • Who can gain access to the data. 

   

Depositing qualitative data

All digital formats. 

  • Give the file(s) a name that is self-explanatory. 
  • Write a table of contents for the files/data that is to be archived. 

Include all relevant information about the project, such as: 

  • Interview guide 
  • Documentation report or other documents related to the data material. 
  • List of data/documents/files in the project so that you have an overview of the data material. 
  • Articles, book chapters, or books related to the data material (PDF document or persistent link/DOI). 
  • Include documentation that the data material can be archived and shared with either indirect or direct personal information (we do not currently accept anonymized qualitative data). 
  • Example: An information letter, a consent form, or documentation from Sikts Data Protection Services, the Norwegian Data Protection Authority, or the Regional Committees for Medical and Health Research Ethics (REK).  

A data processing agreement must also be in place between the research institution and Sikt if the dataset contains personal data.

The data processing agreement should include information about: 

  • The data that is to be archived. 
  • How long the data will be stored. 
  • The purpose of archiving the data 
  • Who can gain access to the data

Contact

If anything is unclear, or if you have any questions regarding depositing data, please contact us: