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Do you have a great idea but just need the right data to test it?

Search the datasets in The Love Consortium Dataverse! The Love Consortium Dataverse is a centralized resource designed to optimize scientific collaborations on social behavior and relationships.


Researchers who post descriptions of their datasets in Dataset Records on The Love Consortium Dataverse have done so because they are open to collaboration with those data. These datasets are a treasure; they have sometimes been sitting without use for more than a decade yet could hold jewels of undiscovered findings. As such, the core requirement for researchers with data is to describe it.

Data seekers like you can search these standardized descriptions to find the types of populations, methods, and constructs best suited for your research question. Once you find a dataset description that holds promise for testing your question, you’ll see if the owner of the data has uploaded supplementary files or not (e.g., table of variables, materials), check out their customized notes about collaborating with that particular dataset, and use the contact button to ask more questions or suggest a collaboration.

What to Expect
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Optimizing Your Search

To get a better idea of how to search for data you are looking for, it may help you to know the fields researchers are asked to complete when describing their datasets. The full list can be found here. Some of those fields – like commonly studied constructs or commonly used methods – use controlled vocabulary to keep things standardized; you can find those controlled vocabulary choices here .
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Ask Questions

The Dataverse Record contains an email address for the primary contact person. Once you have reviewed the description, if you still have questions, reach out!
Tip: If it is a quick question, ask it quickly. If it requires the reader to have some background information, we still recommend including the bottom-line question in the first few sentences of the email or in the subject line.
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Perspective Taking

When composing an email, we suggest following standard professional guidelines (see here ). Consider what will make it easiest for the person to respond. And if you haven’t heard back for awhile, give the person the benefit of the doubt and just assume they’re busy – feel free to send a gentle reminder about your question after a reasonable time has passed.


TLC Datavese


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APA Authorship Guidelines

Communicating early and often about authorship is helpful, and this is especially true when forming a new team of collaborators. The APA guidelines contain reminders of what type of contribution merits authorship and may provide a useful basis for this conversation.
Tools Collaboration
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Example Concept Paper Form

After you have started discussing a possible project, we recommend the lead author pitch a concept paper for review by the owner of the data.  It gives an opportunity to solidify the idea and is something for the data owner to show potential team members who may deserve authorship (and who may have helpful feedback based on their knowledge of the dataset); at the same time, it provides a record of the idea and agreement by all involved.
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Example Memorandum of Understanding

This sample Memorandum of Understanding between the person who owns the data (e.g., the PI) and the person who will be leading a collaboration with those data covers many potential scenarios and provides a template for successful and productive collaborations.
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Considering Pre-Registration

Innovation requires exploration. Nonetheless, through the collaborative use of multiple datasets, The Love Consortium project provides a unique opportunity to combine exploratory and confirmatory analyses. If pre-registration is the right plan for your project, here are two commonly used sites:
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Cite Your Data

Once you create the Dataset Record for your dataset, it will have a permanent digital object identifier (doi). Whereas many researchers are used to citing the first paper they published on a study to refer back to a broader dataset, instead you would be able to cite the dataset itself. The advantages of this are described here.
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Update Your Dataverse Record with New Citations

Keep potential collaborators up to date on what you have learned with your dataset by updating your Dataset Record when there are new empirical publications that use the data. You can do that at the same time you update your CV by quickly accessing the record, clicking “Update”, adding the citation with its permanent digital object identifier (doi) to the “associated publications” field, and submitting the change.
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