If you’re wondering what other enhancements are in the works, check out this page. This provides a tentative (but not comprehensive) list of what’s coming in 2018.
Don’t hesitate to send suggestions via email@example.com. We are listening!
Measure Mode UI/UX improvements
- Assign resources to run aggregates. Currently you cannot easily assign resources to an aggregate of runs. (Actually there is a workaround to do this - as mentioned above - but it’s not a great UX.)
- Hierarchical plate ID search in Plate Transfer tool. When searching for plates using the plate transfer tool, Riffyn does a global search. This is a problem because people often name their plates non-uniquely (their only unique to the experiment, not all experiments). This improvement will first search the local experiment, and only if the plates are not found there will it search globally.
- Saving of plate transfer configurations to a process.
- Show/hide columns in the run table
- Paste columns in the run table
- Expanded search fields when finding input resources (i.e., search ID, barcode, and other common fields where identity information is likely to be stored).
- Merge Plan and Actuals tab (both functions in same tab).
- Add drop down menus in bottom panel for valid options (in addition to free text)
- Expanding the run types to include “reference” and “blank”
- Function to quickly delete multivalued data from a property or column (Currently you must remove the entire uploaded file (if it came from a file) or manually deleting the data in the multi-value data editor run by run.)
- Make the language and layout of column context menus more intuitive
Allow full process editing of any experiments
This is a major upgrade of our versioning system to make it more flexible and more powerful. It will include branching, and eventually, merging. (Like source code control for your R&D processes!)
Kind of like v-lookup in Excel, only a lot easier and better.
Data query and analytics integrations
- Faster data table build on export.
- Fuzzy joins of data across steps on data export. This will allow you to match data within a cluster or tolerance limit, for example, when the time points are not an exact match.
- Data slicing (subsetting)
- Select a subset of columns for export
- Select subset of experiments for export
- Select a subset of rows matching a condition on properties (i.e., the equivalent of a ‘where’ statement in SQL)
- Tableau connector
- Knime connector (a node in Knime)
- Expanded toolset for JMP AddIn
Data acquisition improvements
- Improvements to Parsely so you don’t have to remake your configs when a data file changes slightly.
- Data pivoting capabilities for data acquired via Data Agent
- OSI Pi connector
Microtiter plate and screening toolset enhancements
- Fill-down tools for plate transfer.
- Hit-picking (rearraying function) on plate transfer.
- 2D plate maps
- Scaling of runs per step to >50,000. (Current limit is 8000 runs per step.)
Automatic unit conversion
Automatically convert units on properties to a common one across experiments and in formulas.
Improved browsing and search functionality in the Library
Upgrade and standardization of UI components (buttons, menus, modals) & navigation paradigms