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Data Collection

Selecting the right data collection tool is an important part of planning an Open Science Framework (OSF) project. Different tools offer different strengths in terms of accessibility, collaboration, transparency, and long-term preservation. Two commonly used tools are Qualtrics and Google Sheets.

Qualtrics

Qualtrics Qualtrics is a widely used survey platform that is particularly useful for complex questionnaires, multilingual studies, and projects requiring advanced survey logic. Many Dogs uses Qualtrics for internal surveys of members, external surveys of non-members, and as the primary method to obtain demographic data from guardians in studies.

Advantages of Qualtrics

  • Strong multilingual support, allowing the same survey to be administered in multiple languages.
  • Advanced survey logic, including skip patterns, branching, randomization, and display conditions.
  • Surveys can have designated owners, which helps clarify responsibility for survey management.
  • Supports collaboration among multiple team members during survey development.
  • Surveys can be retained over the long term and reused in future projects.
  • Version control allows users to track changes between published and unpublished survey versions.
  • Professional survey formatting and participant experience.
  • Useful for large-scale studies that require secure data collection and sophisticated design features.
  • Can use APIs to directly download data from R using specific packages [Qualtrics] (https://docs.ropensci.org/qualtRics/?utm)

Disadvantages of Qualtrics

  • Access often depends on an institutional license.
  • External collaborators may face access restrictions if they do not belong to the same institution.
  • Collaborators without subscription access may encounter administrative barriers.
  • Survey metadata and complex survey logic are not always fully preserved in exported files.
  • Formatting inconsistencies may occur when surveys are exported.
  • Additional processing may be required to reconstruct the original survey structure outside the platform.
  • Much of the survey structure remains embedded in a proprietary interface.
  • Limited transparency of backend survey logic can reduce reproducibility.
  • Long-term archiving in a fully reusable and open format can be difficult.
  • If institutional access ends, future editing or management of surveys may become impossible.
  • Can use APIs to download data from R using specific packages directly [Google Sheets] (https://googlesheets4.tidyverse.org/?utm)

Google Sheets

Google Sheets [Google Sheets] (https://workspace.google.com/products/sheets/)is a lightweight and flexible data collection tool, particularly for collaborative projects, shared coding tasks, or manual data entry. Many Dogs uses Google Sheets for behavioral data collection of the dog-focused studies.

Advantages of Google Sheets

  • Data entry constraints can be implemented using dropdown menus, validation rules, and restricted fields.
  • Increased accessibility for international collaborators because only a Google account is required.
  • Lower administrative barriers compared to institutionally licensed software.
  • Data can be easily exported to CSV and other open formats.
  • Reduced dependence on institutional contracts or subscriptions.
  • All collaborators can directly access, edit, and review the dataset in real time.
  • Built-in version history allows users to track changes and recover earlier versions.
  • Useful for collaborative coding, data cleaning, and project management.
  • Supports comments and discussion directly within the spreadsheet.
  • Integrates easily with other open tools and workflows.

Disadvantages of Google Sheets

  • Limited support for complex survey logic compared to dedicated survey platforms.
  • Data quality may be affected if collaborators accidentally overwrite, delete, or modify entries.
  • Requires careful management of editing permissions to prevent errors.
  • Not ideal for highly sensitive or confidential data because of privacy and security concerns.
  • Large datasets can become slow and difficult to manage.
  • Spreadsheet structures can become inconsistent if collaborators use different naming conventions or formatting styles.
  • Dropdown menus and validation rules may not be consistently maintained over time.
  • Changes to formulas or variables may not always be immediately transparent to all collaborators.
  • Metadata documentation is often incomplete unless researchers create a separate codebook.
  • Google Sheets depends on a proprietary platform and internet access.
  • Long-term preservation may be challenging if files are not regularly exported to open formats such as CSV.
  • Simultaneous editing by many users can sometimes create confusion or conflicting changes.