In most research projects time for innovation is short.
Novel research can only happen after months of data discovery, data collection, integration, and quality assurance. In data-intensive research, scientists can spend up to 80% of their time on data management tasks alone.
We can change that.
wetransform typically gets involved during the proposal phase of a research project in one of two ways:
During the project, we continually improve data management. Functioning similarly to a Scrum Master in software development, we resolve roadblocks and improve efficiency wherever possible.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
From day one, all project partners use the data set manager to upload data. This enables the researchers to find relevant data swiftly. We support versioning and branching, which makes it easy to stay up-to-date.
Over 30 Successful Projects
Olav Peeters Belgian Interregional Environment Agency
Dr. Joachim Rix Smarticipate