Share Research Work

How to share information across the R&D department ?

Let's present below some tips and methods to avoid errors, stress and reach "Real Time" through 3 scenarios of efficient collaborative work:

• Order biotech analysis and retrieve the MM results.

• Share field trial work with technicians.

• Communicate variety and hybrid performances with the product development department.

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The researcher at the center of information sharing

Researchers share research information with other persons, or laboratories, inside or outside their organization.

Also, notably in life science, researchers need to take in account the life of the studied objects in the past, at least how have been produced these objects, or if apparented objects, like parents objects, have been studied in past years.

Now, once researcher is able to gather all these information on the life objects, from several experiments, and from experiment done in the past, he must verify the good quality of the data to make decision for the future.

To this aim, a user-friendly research software helps !

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Information system challenges for data sharing

Best practices in the IT system management guarantee the efficience of data sharing, such as integrating cross-functional collaboration to your R&D.

1. The first one is about the quality, notably centralization and normalization of data. For example, standardized processes ensure the homogeneity of data: same codification rules, same variables, same methods.
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2. The second one is about the confidentiality ; security and confidentiality between Activities (Breeding and Testing), Crop teams (Wheat team or Corn team), and Department (R&D, Sales, Management), for instance thanks to data access rules or presentations.
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3. The third one is about the technologies used to exchange data, import/export from devices (automatic synchronization) and easy web access to some commercial or public data.

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3 scenarios of exchanges in your research department

Share testing work between trial manager and technicial

A trial manager and a technician share information and collaborate in a data collection process thanks to RnDExp®:

The manager has access to all features of the trial management platform.

He prepares the trial network, sends data collection requirements and eventually asseses result reports.

The field technician only accesses the data collection interface.

He follows the instructions and sends back the data scored :

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Breeder and laboratory sharing biotech information

A common database and compatible processes enable collaborative work from nursery sample picking to analysis.

The breeder runs his plant breeding processes, he prepares the nurseries and requests analyses on a selection of progenies.

The lab technician only accesses the lab interface.

She follows the instructions, proceeds to the analyses and sends back the results.

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Share research work with product dev and sales teams

Information from the research database is always sensible, usually secured in a digital safe.

An accurate right management along with best practices of research database structure enable to share information with third parties.

The sales department has much to gain in working together with the research department:

They access specific information such as variety and environment reports, web mapping of results... which helps much to produce the classical "Brochure report", including notably PCA statistics for agronomy.

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In the end, what are the benefits of research collaboration?

• Sharing research data and resources in real time allows researchers to react faster. Pretty handy to adjust task advancement under breeding process hazards for instance!
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• Unifying research know-how also benefits to the whole R&D department: Best practices spread, allowing breeders to compare different methods and define some standards to improve the efficiency of the work and save time.
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• Collaboration between researchers improves indirectly the quality of data exchanged, and reduces the redundancy of data production to save resources and investments.
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• Centralize and compile data from multiple sources (phenotype, genomic, environment...) empowers plant breeders to take the best decisions.

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The content of this article comes from a webinar presented by Rudy MEZINO, Agronomist and business engineer at Doriane®, with real case studies using RnDExperience®.