"creator": Screenshots of the data entry for DD Creator, including overall variable and individual level attributes. JSON files can be easily imported, indexed, and shared through sites such as Google Dataset Search. The code block on the right shows an example. Specifically, data is encoded as name/value pairs. Codebook What is JSON? JSON, which stands for JavaScript Object Notation, is a machine-readable file format used to represent data. Data dictionaries are one component of this broader effort. Visit the site at For psychological research, current standardization efforts include the Psych-DS project (Kline, 2018) 5. Google Dataset Search, which is connected to, allows researchers to index their datasets using metadata and the JSON file format (see below). One benefit of such standardization is the ability to index one’s dataset so that other researchers can easily find it. It provides a community-based set of standards for structured data. Why standardization? is a website that provides structure for what can and should be included in metadata. This application allows users to create an HTML report, a JSON file formatted to follow guidelines for datasets from, and CSV files of their metadata. Users can also enter information about dataset properties such as authors and collection dates, according to recommendations. On a separate page, category labels can be provided for both character and numeric data (i.e., Likert-type scales that include labeled numbers). A description of each column can be added, along with information about the levels/groups in the data and synonyms for the variables. What is open science? A collaborative effort to make the research process more public Encouragement of transparency throughout all stages of the research process (Nelson, Simmons, & Simonsohn, 2018)1 Open data discourages fraud and makes replication more likely (Piwowar, 2013) 2 Why data dictionaries? Data dictionaries are documents that contain metadata about a dataset They allow researchers to make data more open and easier to interpret Several dictionary creation apps depending on researchers’ needs Codebook DD Creator Citation Arslan (2018) 3 (DeBruine, Buchanan, & Mohr, 2018) 4 Input CSV, SPSS, Stata, RDS CSV, Text, Excel, SPSS, SAS Output HTML report from Markdown CSV files of meta-data, JSON, Rdata, HTML report Benefits Easiest to use Quick metadata generation Generates a summary for each variable in a readable format Follows Specifies a separate section for category labels Rdata output More detailed descriptions, depending on data DD Creator allows a user to enter metadata for each column provided in the dataset, while automatically providing a starting point for the number of unique values, missing values, variable type (i.e., character, numeric), and minimum/maximum values. Finally, the data dictionary is stored in an online repository, such as the Open Science Framework or GitHub, to share with a larger audience. Next, the dataset is converted to a data dictionary by using an application, like Codebook or DD Creator, that creates the metadata output in JSON, HTML, or another format. The left side starts with the rules or structure one should follow for creating a machine-readable data dictionary. Buchanan, PhD Missouri State University, Harrisburg University of Science and Technology Summary DD Creator Data Dictionary Workflow Do we still like the title? The flowchart below depicts the process of creating a data dictionary. Getting Started Creating Data Dictionaries: Creating Shareable Datasets Ari L.
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