How to use the NTR Data Showcase

To access the NTR Data Showcase, a login is  required. Login  credentials can be requested from NTR data management.

The Data Showcase was designed to give users insight into the data available within the NTR. Each item in the Data Showcase is a variable from one of the NTR research projects. All items are labeled and tagged with keywords and organized into domains using the Maelstrom taxonomy. 

If you are planning to submit a data sharing request, you can use the Data Showcase to collect the variables you would like to request in a shopping cart and export them to a JSON and/or CSV file. These files can be submitted to NTR data management as part of your data sharing request. For more information on how to submit a data sharing request, see Submitting a data request.

Searching by keyword

You can search for items by typing a query in the search box. You can just type a keyword or create more advanced queries using, e.g., 'and'/'or' operators and wildcards (%). More information about how to compose a query can be found under the i button on the Data Showcase website.
Above the "filter by research type" box, the application will show you how your query is being interpreted - if this is not what you wanted, change the query and try again.

DSC

Searching by ontology

It is also possible to search through the ontology tree on the left, under “select domain”. Each item in the database has been assigned a domain. When a tree node (e.g. “diseases”) is selected, the selection on the right is limited to items within that domain. It is also possible to filter items by name by typing a keyword into the search box above the ontology tree. For example, if you type “diseases” in the search box, the tree will show all items with the word “diseases” in the label.

Note that each item can be assigned to only one domain! For example, an item that could be classified as a psychiatric measure but also as a behavioral problem will be found under only one of those two domains. Therefore, to avoid missing items, it is generally advisable to filter the tree based on keywords. This ensures you will find every item with that keyword in the label, regardless of how it was classified.

Filtering results by project or type of study

If you are specifically looking for items collected in the context of a specific project, you can narrow down your search results by applying filters.
You can “filter by research type”: this  distinguishes between studies in adults (ANTR) and children (YNTR, these are mainly parent and teacher reports). You can also “filter by project”. Here you will see the name of the projects and their project codes (for an overview of the projects and project codes, see NTR research projects).

Viewing more detailed item information

By clicking the ? button for an item, you can request the item summary which gives you more information on the variable, including Dutch and English variable labels, variable type, keywords and number of missing values.

Collecting and exporting items (in JSON or CSV format)

To select an item, check the box and add it to your shopping cart. Once all your items are in the shopping cart, you can export them. Two file formats are available: .JSON and .CSV.
The .JSON option exports a list of item names in JSON format that can be used by NTR data management to create your dataset.
The .CSV format is a more readable format that specifies the project, label and sample size. This format is used by the data access committee when reviewing a data sharing request.

When you submit a data sharing request, make sure you include both a .JSON and .CSV file as part of your application.

Editing a previous selection

To modify a selection you have made previously, you can upload an existing .JSON file back into the Data Showcase. This will put all items in the .JSON file in the shopping cart. To edit your selection, add items to the shopping cart, or remove some, and export your updated selection to a new .JSON file. Please note: only .JSON files can be imported, this is not possible for .CSV files.