Successful external R and D collaborations
Djuli is built on the tenet that experimental collaborations within teams and between teams are more powerful than experimentalists working alone or teams that are not efficiently connected. A key feature of Djuli is the ability to increase the ENV of any experimental...
Searching through Experimental Data
It is not uncommon that two years into a large programme that experiments can start to be repeated and so it is very important to know where the data is and to be able to search the historical record, both to remember and learn from the past and not to duplicate past...
Structuring your Experimental Data
Djuli has a structure consisting of Cluster, Projects and Reports. At the top level of the Djuli structure are Clusters, these are set up by the Senor Experimental Manager, and imposes the organization structure in which the experimentalists will build the content...
Where to and where not to store your experimental data
A common issue in many organizations is that individual experimentalists could be saving their data in different repositories or silos, or in the worst case on local computer drives, which are not backed up. Though generic Cloud storage (One Drive, Google drive and...
Understanding your Experimental Network Value
The Experimental Network Value (ENV) is the value of your experimentalist network based on the number of experimentalists within your internal and external networks and is calculated based on the assumption that your scientists/engineers/experimentalists can see each...
Unlocking the value of your experimental efforts
The big issue during any R and D effort is unlocking the full value from your experimental resources. The Experimental Network Value (ENV) is a measure of how powered your R and D efforts are, and is a function of the number of experimentalists/scientists/engineers...