How we solve your problem
Keep it organized
Research data management is critical for FAIR data, especially when it comes to releasing data into public access. Sci2sci offers a flexible yet structured way to organize it. You can easily split the work between users and aggregate separate participants' contributions, publishing results on the go - whenever you feel ready to release them into public access.
E.g. Prof. Albert is the head of a big research lab with multiple international collaborators. Using sci2sci, all project-related data can be easily stored in one place, with all the contributors to each data piece receiving relevant attribution. Whenever a particular research project is ready to be released into public access (e.g. with a manuscript publication), all the relevant original data can be published in one click, in compliance with most journals and grant funders' policies on open data.
Share and search efficiently
We use advanced algorithms to improve discoverability of published datasets and relevance of the results during search. We support full text search, search by synonymous entries and search by structural similarity. Our platform indexes the description provided by the user but also parses the content of the uploaded datasets, which means the data content itself (and not only metadata/description) will contribute to the dataset rank in the search results list.
E.g. Bella has been developing synthetic viruses for a decade, and published her research data at the university repository. However, this data was difficult to find and therefore was not reused by other researchers. Bella applied to sci2sci for indexing her data, and her dataset was found by a large biotech company that was looking for new gene editing technologies. Bella now serves on the advisory board for the project to deliver genes via synthetic vectors.
Observe the impact of your contributions
Sci2sci is bringing tools to provide users with metrics - how many people viewed their data, downloaded it and reused it in derivative works. Moreover, people can comment on published data, giving room for discussion and intellectual collaboration.
E.g. Carl and David developed a new technology of “self-healing” concrete that would be re-establishing its properties whenever cracks appeared, but they couldn’t find a good way for economical mass-scale production. They deposited data about their research on sci2sci platform. Now, two years later, their data has been reused and cited multiple times, with two publications claiming they have improved the technology to make it available for mass production, and one crowdfunded company trying to bring this technology to the market.
Receive personalized updates
Whatever your research topic is, stay tuned for the most recent data published in your field! We can provide you with personalized notifications based on the keywords or their unique combinations, type of the published files etc.
E.g. Erik is investigating the role of semaphorin 3A protein during early development of the mouse brain, and he is particularly interested in the proteomics data. To stay up to date with the latest discoveries relevant to his research, Erik subscribes to receive notifications when datasets with keywords “SEMA3A” & “embryonic mouse brain” & “omics”, or “SEMA3A mutations” appear online.