Sharing and Collaborating on Knowledge for Scientists
Kyso for Teams is a centralized knowledge hub for sharing and collaborating on research and analyses in the lab
A Problem of Knowledge Management
Sharing knowledge a fundamental aspect of science, but sharing insights from data analysis in a way that is easily discoverable and reproducible can be challenging.
While the scientists in a lab work on the same or similar problems, working towards a common goal, they often differ in the software and tools they use to conduct experiments and run analyses.
Consider the following, a team of researchers, working on common projects, all using various file-types, from Excel Workbooks, Google Docs, and PDFs to PowerPoint presentations that contain charts generated from software tools like MATLAB or Jupyter notebooks.
All of these files are saved to an internal server, on which access can be granted by file owners. The problem?
- No discoverability — you can find a file if you know where it is, but its really hard to just browse and understand what colleagues are working on.
- Discussion — file servers have no space for commenting on each others work.
- No version control — as files are updated over time, previous versions of work are lost.
- No reproducibility — the code used to produce analyses is often inaccessible.
- Email? — this almost always means that the analysis and discussion can’t be discovered or referenced later on.
Our solution: Kyso for Teams
While scientists will continue to work with different tools and documents, having a common framework for communicating and collaborating effectively can accelerate the progression of a lab’s research goals. Thats why we built Kyso.
Kyso is our centralised knowledge-sharing platform for research teams.
Think of it like Medium — an elegant, internal, blogging platform, but with the added benefit of being compatible with technical tools like Github, Jupyter & R notebooks. We built Kyso to keep your knowledge in one place so the entire lab can learn from the team’s research, in a way which is easily discoverable.
In building Kyso, we focused on a few points to achieve this:
- Readability: Insights must be presented in a well-documented format. Analyses are rendered as beautiful data blogs, in which code can be both hidden and shown, that is digestible to both technical and non-technical readers.
- Easily Searchable. A comprehensive tagging system for managing your projects & content upvoting, which acts as an auto-indexer for research topics and posts, keeping content structured and current for organizing and discovering the work of other contributors.
- Flexible publishing: Write articles, upload charts, code, datasets, links, and Jupyter & R notebooks. We are also fully integrated with Github, for those of you used to more command-line workflows.
- Open collaboration: Blog-style commenting for feedback, suggestions, and discussion. Not via closed email.
- Easy of use: A simple, but aesthetic, UI and comprehensive documentation.
- Reproducibility: Ability to fork posts & extend analyses or continue working on them as part of new research, so team members can duplicate results, extend analyses & set new projects in motion much faster.
- Easy user management: App-based team access controls for managing who can post, edit or simply consume content.
Conclusion
Sharing knowledge is one of the most important tasks you do as a scientist, and Kyso is our attempt to make that process easier and more efficient. So give it a try today and start your team on Kyso.
