How to Overcome Data Reproducibility Crisis?

Introduction of digital lab books have replaced paper based lab notebooks. However, both of them could not quell the physical hardship of data entry. This means irrespective of lab books being either digital or paper based the human error will still prevail. Surprisingly these errors quickly accumulate into a "data reproducibility crisis" that has tampered the reputation of institutions and scientists. For example, on 3rd January 2020, the Nobel Prize winner Dr. Frances Arnold had to retrieve her publication from the prestigious Science magazine, as the published data was not reproducible by her peers. Thanks to her remarkable display of honesty as she admitted that the retrieval was due to her busy schedule and oversight on data reporting process. Dr. Frances had trusted the conventional mechanism of data management in the lab - manual data entry. There are several similar cases in science, that has failed the professors, R&D managers, institutions and companies at large. Then, how to improve trust on data reporting process? "Automation" is the solution. 

"Ducom's MOOHA opens up tremendous intellectual space for creativity among scientists, as they no longer have to spend time on data collection and traceability"- Prof. Shrikant, University West, Sweden

We have carefully designed a digital solution by empathizing with the professors, to resolve the "data reproducibility crisis" in science. MOOHA is that digital solution powered by IoT and A.I. that can automate several critical steps during experimentation and the raw data is instantaneously digitized into a lab book. Automation means there is no room for human error in managing the "raw data". MOOHA will be the new digital lab assistant that will eliminate oversight and bridge the trust between "busy" professors and stake holders in the lab. (watch this 30 sec video below to understand what motivated us to build MOOHA?)

1. Automation of data logbook enables quick recall of historic data in seconds from any part of the world
2. Remote access to live data from multiple laboratory instruments helps continuously monitor the test conditions
3. Statistical analysis of big data within seconds can prevent error in data handling between platforms
4. Centralized reports for every projects assured with traceability of data accelerates the rate of decision making
5. Data driven forecasts of lab performance and expenses helps in yearly budgeting
6. Enhance confidence and transparency with your collaborators through data sharing and live updates about experiments
7. Remote learning using AR powered digital twins of lab instruments can help to quickly understand the functionalities in the lab instruments