Open Data Community Survey 2025

Introduction

This survey deals with open data and semantic metadata. It is funded by the DDI Alliance. If you use or provide open data (or might in the future), please complete this survey to share your perspectives. View important information about your consent to participate by clicking on the following link: Survey participant information and consent form (you are encouraged to save or print a copy of this document).

Please share the link to this survey with individuals and organizations in your networks. However, there is no obligation for you to pass along this invitation, and there will be no penalty to you if you do not share it. Estimated time to complete the survey is 15-20 minutes.

This survey has been approved by the Research Ethics Board at the University of Regina. By continuing, you confirm that you give your consent to participate and that understand what this consent entails.

Demographics

The following questions ask for some information about you and your organization (if applicable). If you are affiliated with more than one organization, indicate the one where you are most involved with open data.

  1. Please select the option that includes your age

  2. Please indicate your gender

  3. Please select the option that best describes the highest level of education that you have completed

  4. Please select your country of residence from the dropdown

  5. Please indicate your level of expertise with open data

  6. Please indicate your level of expertise with semantic metadata standards (e.g. DDI, DCAT, Schema.org, Dublin Core)

  7. Please choose the option that best describes your organization

  8. Organization name

  9. Organization website

  10. Does your organization publish metadata that complies with FAIR or other open standards?

  11. Does your organization use any metadata standards?

  12. Please describe the metadata standards used by your organization

  13. What tools, resources, or support would help your organization adopt metadata standards like DDI?

Open Data

Open data is defined in the following way: “Data is open if it can be freely accessed, used, modified and shared by anyone for any purpose - subject only, at most, to requirements to provide attribution and/or share-alike.” The following questions ask about your experience with open data and your level of agreement with some statements about open data.

  1. How frequently do you work with open data?

  2. What fraction of the data with which you work is open data?

  3. Have you ever encountered a lack of technical support while working with open data sources, tools, or platforms?

  4. Please list the websites, email lists, groups, and professional societies that you access in your work with open data

  5. Are you familiar with the 5 star scale for linked open data?

  6. Are you familiar with the FAIR data principles?

  7. Are you familiar with the Open Data Charter?

  8. Are you familiar with the Sebastopol Open Government Data Principles?

  9. Are you familiar with DDI or other metadata standards?

Please rate your agreement with the following statements

  1. Open data should be freely accessible, in a machine-readable format, freely usable without licensing restrictions, and free of charge

  2. Open data should be “AI-Ready”

  3. Technical openness (standards and interfaces) is an important aspect of open data

  4. Legal openness (copyright and licensing) is an important aspect of open data

  5. Commercial openness (commercial use of data) is an important aspect of open data

  6. There is a place for non-open data that follows the FAIR principles, for example

  7. Data sovereignty can be addressed within the context of open data

  8. Open data increases government transparency

  9. Open data enables economic growth and innovation

  10. More public awareness about open data is needed

  11. Open data contributes to democratization of data

  12. It is possible for open data providers to have a say in the use of their data in AI or IoT (Internet of Things) applications

  13. It is possible to prevent misuse of open data by generative AI systems

  14. Generative AI tools contribute to flooding the web with untrustworthy or misleading data

  15. Open data is trustworthy

  16. Non-open data is trustworthy

  17. FAIR metadata standards like DDI, Schema.org, and DCAT improve trust in open data

Your Role

The following question asks whether you use open data provided by others, provide open data to others, or both.

  1. What is your primary role with respect to open data?

User

Please answer the following questions from your perspective as a user of open data

  1. What fraction of your time is dedicated to using open data (finding, leveraging, visualizing, analyzing)?

  2. Check all that are important to you when thinking about data quality

  3. How do you describe the average quality of the open data that you have used?

  4. Is the quality of the metadata a good indicator of the data quality?

  5. Is the inclusion of valid emails and valid HTTP/HTTPS URLs for access and contact, a good indicator of the data quality?

  6. Is the adherence to open data principles (open file format, open license, and machine readable) a good indicator of the data quality?

  7. Have you ever encountered problems with data or metadata quality?

  8. Have you ever encountered legal problems with respect to restrictive, unclear, or complex licenses?

User’s most-used source

Please answer the following questions about the open data source that you use most

  1. Name or URL of your most-used source

  2. What is your purpose for accessing your most-used source?

  3. Which programming language do you use to access your most-used source?

  4. Which frameworks or standards are used in your most-used source?

  5. Are you able to use the data that you find at your most-used source?

  6. Are you able to reuse the data that you find at your most-used source, in whole or in part?

  7. Is it easy for you to access, use, and reuse the data that you find at your most-used source?

Provider

Please answer the following questions from your perspective as a provider of open data

  1. What fraction of your time is dedicated to providing open data (creating, publishing, collecting, storing, stewarding)?

  2. In which formats do you provide/publish open data?

  3. Please specify in which other formats you publish open data

  4. Have you ever encountered privacy or security concerns when deciding to provide open data?

  5. Have you ever encountered problems related to strategic or business decisions when providing open data?

  6. Have you ever encountered problems related to legal constraints when providing open data?

  7. Have you ever encountered any technical barriers in providing open data?

  8. Do you encounter challenges with interoperability in applying metadata standards?

  9. Do you encounter challenges with tools when applying metadata standards?

  10. How important is metadata interoperability for open data reuse?

The following questions relate to the FAIR data principles. For each principle, rate its importance and ease to accomplish

Metadata and data are assigned a globally unique and persistent identifier

  1. Is this important?

  2. Is this easy to accomplish?

Data are described with rich metadata

  1. Is this important?

  2. Is this easy to accomplish?

Metadata clearly and explicitly include the identifier of the data they describe

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data are registered or indexed in a searchable resource

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data are retrievable by their identifier using a standardised communications protocol

  1. Is this important?

  2. Is this easy to accomplish?

The protocol is open, free, and universally implementable

  1. Is this important?

  2. Is this easy to accomplish?

The protocol allows for an authentication and authorisation procedure, where necessary

  1. Is this important?

  2. Is this easy to accomplish?

Metadata are accessible, even when the data are no longer available

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data use a formal, accessible, shared, and broadly applicable language for knowledge representation

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data use vocabularies that are findable, accessible, interoperable, and reusable

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data include qualified references to other metadata and data

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data are richly described with a plurality of accurate and relevant attributes

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data are released with a clear and accessible data usage license

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data are associated with detailed provenance

  1. Is this important?

  2. Is this easy to accomplish?

Metadata and data meet domain-relevant community standards

  1. Is this important?

  2. Is this easy to accomplish?

Provider’s most-recent project

Please answer the following questions about your most recent open data provision project

  1. What is the name of your most-recent project?

  2. Does your most-recent project have a URL? If so, please provide it here. If not, please provide a brief description of your project

  3. When did your most-recent project begin?

  4. When did your most-recent project end, or is it ongoing?

  5. What was your goal in creating open data with semantic metadata in your most-recent project?

  6. How did you evaluate the success of your most-recent project?

  7. Which tools, standards, or frameworks (metadata and otherwise) were used in your most-recent project?

  8. What advice would you have for others considering a project using open data?

Open-ended questions

  1. Please describe any gaps that you perceive in policies or tools to support open data

  2. What do you perceive as the biggest threat to quality data on the web and is there a way to mitigate it?

  3. Would you like to communicate anything else?

Confirm submission

  1. You have reached the end of the survey. Please confirm your intent to submit your survey responses

  2. Are you certain that you wish to withdraw?

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