Thriving data cultures prioritize inclusion, collaboration, and transparency over command and control. They work iteratively vs. trying to "boil the ocean." But of course, this is easier said than done, right?
Dec 2022 How to fuel innovation with agile data governance
Last Updated: November 1, 2017
data.world is a global community of people passionate about data, discovery, and collaboration, and together we believe we can achieve our mission to build the most meaningful, collaborative, and abundant data resource. We challenge our members and employees to hold themselves and each other to the highest standard of collaborative and respectful behavior. Our expectations of that behavior are covered in these guidelines.
If you find yourself in what you think is a gray area, please consider the best interests of the data.world community before taking an action and feel free to reach out to us.
Follow the Golden Rule. Treat others on data.world as you would like to be treated. This includes treating others’ datasets, projects, comments and feedback as you would like your datasets, projects, comments and feedback to be treated.
Respect others. Everyone on data.world has a different personal background, experience level working with data, and point of view. Our differences make us stronger and should not divide us. As such, treat others with respect and dignity, assume their good intentions, give them the benefit of the doubt, disagree without being disagreeable, be constructive, do not engage in personal attacks, and do not use profanity.
Keep it clean. Do not upload nudity, pornographic, violent, or hateful imagery. We do not tolerate content that condones or encourages bullying, discrimination, violence against people or groups or other harassment of any kind.
Be careful in the words that you choose. We are a broad community of individuals across many disciplines, so we need to conduct ourselves professionally. Understand that words often hold different meanings to many different people and try to be cognizant of other viewpoints. Do not insult or put down other members. Harassment and other exclusionary behavior aren’t acceptable. This includes, but is not limited to:
Violent threats or language directed against another person.
Discriminatory jokes and language.
Posting sexually explicit or violent material.
Posting (or threatening to post) other people’s personally identifying information (doxing).
Personal insults, especially those using racist or sexist terms.
Unwelcome sexual attention.
Advocating for, or encouraging, any of the above behavior.
Repeated harassment of others. In general, if someone asks you to stop, then stop.
Respect intellectual property. Only upload to data.world content that you have the legal right to upload. When uploading a dataset that you did not create or own, be sure to follow the requirements for its license (which usually requires clear attribution), and select the proper license setting on data.world to reflect the license from the original data source. If you are unsure, ask the creator of the dataset. See also our licensing FAQs.
Respect privacy. Do not make datasets public if they contain personal information. Some examples of this type of information include datasets containing Personally Identifiable Information (PII), Protected Health Information (PHI), or Personal Financial Information (PFI). Before uploading any personal information that is regulated, you must enter into a separate agreement with us to upload that type of information
PII (Personally Identifiable Information) is information that either alone or in combination with other information could be used to identify, locate, or contact an individual. Some examples include: a person’s name, a person’s address, a person’s email address, a person’s social security number, or a person’s credit card number.
PHI (Protected Health Information) is information about health conditions, treatments or procedures a person has undergone, or payments someone has made or collected that can be linked to a specific person.
PFI (Personal Financial Information) is information about financial condition, transactions, or activities that a person has undertaken that can be linked to a specific person.
When we disagree with one another, try to understand why. Disagreements, both social and technical, happen all the time. It is important that we resolve disagreements and differing views constructively. Remember that we’re different. The strength of community comes from its varied participants from a wide range of backgrounds. Being unable to understand why someone holds a viewpoint doesn’t mean that they’re wrong. Don’t forget that it is human to err and blaming each other doesn’t get us anywhere. Instead, focus on helping to resolve issues and learning from mistakes.
Do not spam. Do not upload, post, or transmit unsolicited email, SMSs, or “spam” messages or create accounts, datasets or projects solely to increase your search engine results.
Be honest. Work honestly and transparently. Recognize contributions by others and give credit where it is due. Do not upload hoax datasets or datasets intended to deceive others.
Be informative. Create accurate and detailed dataset titles, descriptions, and metadata when uploading datasets so others in the data community or in your network can find, collaborate on, and use this data.
Be collaborative. Invite others to work with you on your projects early on. We have an opportunity to solve complex problems by coming together and bringing our unique perspectives, goals and visions to the solution. Getting that collaboration started early on reduces redundancy and improves the quality of the end product.
Ask for help and help others. No one has all the answers nor all the facts. Asking questions early avoids many problems later, so we encourage you to ask questions to the community and of us. At the same time, if you can help others, do so – share your knowledge, answer questions and support your fellow member on data.world. By working together and helping one another, we can solve what was once unsolvable.
Step down considerately. When you withdraw as a collaborator on a dataset or project or from an organization, please do so in a way that minimizes disruption. Inform the group that you are leaving and take steps so that others can pick up where you left off.
Reporting. If you have any complaints or difficulties with someone in the community, please let us know at email@example.com. We’ll do our best to ensure that your concern is addressed in a timely and effective manner. If, for whatever reason, your email isn’t answered in a timely fashion, feel free to open a ticket on the system and let us know!
Consequences. We take non-compliance with these community guidelines seriously and may take the following actions for breaches of it:
First infraction: Verbal and/or written warning. Everyone slips up or acts out of frustration at times, we just ask that you work to not repeat the behavior.
Second infraction (or more serious first offense): Posting of an anonymized summary of the interaction to educate our community and serve as a reminder that adverse behavior will not be tolerated.
Third infraction (or especially serious first offense): Temporary suspension from all avenues of data.world community participation for four weeks. This includes, but is not limited to, https://data.world, Slack, forums, or any other property owned or associated with data.world.
Continued infractions will be dealt with on a case-by-case basis and can result in permanent suspension from the data.world community.
Regardless of the above consequences, if we determine that the violation of these community guidelines is flagrant or egregious, we reserve the right to take immediate action, including permanently deleting the member account and related files, datasets, projects and/or comments without advance notice or warnings.