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Frequently asked questions

Adding a dataset to ODC-SCI

Add data to a template extracted from an uploaded file

Add data to pre-existing template

Helpful hints


Adding a dataset to ODC-SCI

Overview: You must be a member of a verified laboratory and agree to ODC policies and principles to add data sets to ODC-SCI.

Dataset = Template + Data: In order to help SCI researchers make their data FAIR, ODC-SCI has implemented a data upload workflow based on templates. Templates represent the set of data fields you have collected or are planning to collect. In a spreadsheet, the template would be the collection of column headers. Data sets are created in ODC-SCI by adding data to templates. Templates can be created manually or they can be extracted from existing data files.

Why does ODC-SCI use templates instead of just allowing researchers to upload their data files directly? The goal of ODC-SCI is to create data that are FAIR: Findable, Accessible, Interoperable and Reusable. Templates directly address the Interoperability requirement in two ways. First, templates can be reused by other members of ODC-SCI. When templates are re-used, data sets can be more easily combined, because data has been collected according to the same data model across data sets and laboratories. Second, ODC-SCI encourages researchers to use the Common Data Elements (CDE’s) when creating a new template or to map existing templates to CDE's. Common Data Elements also make it possible to aggregate data, because they indicate what fields two data sets have in common, even if they use different templates. So CDE's make it possible to answer a question: What is the average age of all rodents used across ODC SCI?

Once you have created or selected a template, you can add data to it and share it with your lab members. Sharing data with ODC-SCI or the public requires permission from the lab head.

Summary of main steps for adding data:

  1. Create a template:

    All data is added to a template. The templates are essentially the names of the data fields that you have collected. Templates can be created manually or they can be extracted from existing data files. ODC-SCI encourages researchers to use the Common Data Elements (CDE’s) when creating a new template. For existing data, ODC-SCI provides the ability to map data fields to the CDE’s.

  2. Map template data fields to Common Data Elements (CDE) if necessary

    A Common Data Element (CDE) is a data element that is common to multiple data sets across different studies. In most spreadsheets, the data element is the name of the data field, e.g., age. ODC-SCI has agreed on a list of CDE’s that either should or can be collected in a given experiment. Using CDE’s makes it easier to combine data across experiments and experimenters.

  3. Add data to template (note data must be in CSV format)

    Upload your data to the template. CSV stands for comma separated value and is an open format for spreadsheets. Most spreadsheet programs, including Excel, allow you to convert to CSV by choosing the “Export” option or “Save as” option, and select CSV as the output.

  4. Share with other lab members

    Share your data with other members of your lab. Although ODC-SCI encourages labs to share data with other members and the public, doing so requires permission from the PI.

Detailed instructions on adding data

Create a template

Select Add data --> Create new dataset, then select a method for creating a template. ODC-SCI provides 3 ways to create a template to which to add your data.

  1. Extract a template from an existing data file: If you have an existing data file in CSV format*, choose “Upload file” and ODC-SCI will extract the column names from the spreadsheet.
  2. Select an existing template: If you already have templates stored, select one from the library presented.
  3. Create a new template for collecting data: If you haven’t collected your data and would like to create a ODC-compliant form, choose "Create a template"

Method 1: Add data to a template extracted from an uploaded file:

What you will need:

  • Data file in CSV format.
  • Make sure that the first row of your spreadsheet contains the names of the data fields.
  • Make sure that any field labeled "notes" is deleted, as ODC-SCI does not allow import of notes fields.
  • You will also need to know which fields contains the list of subjects.

What you will do (see visual tutorials for each step below):

  • Go to "Upload your data"
  • Upload file to extract template
  • Prepare your template/map to CDE's
  • Upload your data to the template
  • Share

Go to "Upload your file"

Upload your file to extract template

Prepare your template by selecting subject field, arranging your data fields and data fields to CDE's

Upload your data to the template

Share your data with lab members

Method 2: Add data to pre-existing template:

What you will need

  • Data file in CSV format.
  • Make sure that the first row of your spreadsheet contains the names of the data fields.
  • Make sure that any field labeled "notes" is deleted, as ODC-SCI does not allow import of notes fields.
  • The name of the template you wish to select

What you will do (see visual tutorials below)

  • Go to Add data > Create data set > Use existing template
  • Select the template from your library
  • Preview the template
  • Name your data set and prepare template for data upload
  • Upload your data to the template
  • Share your data file

Go to Add data > Create data set > Use existing template



Select the template from your library
Preview the template to ensure it is the correct template for your data



Name your data set and prepare template for data upload


Upload your data to the template


Troubleshooting data upload



Share data with lab members


Helpful hints

  • Before you upload your data:
    • Make sure the file is in CSV format (?)
    • Check that there are no duplicate data field names
    • Make sure there are no empty rows before the field names
    • Make sure there are no leading underscores or spaces in the field names (e.g., _date is not allowed).
    • Minimize the use of special characters in field names (other than _ or -)
  • Naming a dataset: The more descriptive the title, the better. Data from MIASCI study is better than "Joe's data"
  • Naming a template: The more descriptive the title, the better. MIASCI2008 is better than "Joe's template" if you want to spur reuse
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