LabFriend
Laboratories collect and document information from experiments, not only to understand results but also to reuse, share, and build upon that knowledge. In the era of digitalization of experimental facilities researchers are expected to enter (meta)data into Electronic Laboratory Notebooks (ELNs), the digital equivalent of paper lab notebooks. While ELNs are an important tool for modern science, completing them by hand is time-consuming, prone to errors, and typically causes undesired interruptions. These challenges make it harder to implement widespread and successful use of digital laboratory tools, which in turn hinders the creation of high-quality, reusable laboratory data. To address these issues, the LabFriend project is developing a smart assistant system that helps scientists enter (meta)data into ELNs more effectively and with fewer errors. The goal is to make data entry easier while also improving the consistency and usefulness of the information collected.
There are two features we are developing within LabFriend. First, form-filling assistance will give real-time suggestions as users type, reducing time spent on the task, avoiding mistakes, and promoting consistent terminology usage. Second, we will enable hands-free data entry using speech recognition, allowing data to be dictated to into the ELN without unnecessarily interrupting laboratory activities. LabFriend is designed to work with semantic technologies, which means the assistance system can understand and use the structure and meaning of scientific terms. This helps make the data more searchable, easier to connect across projects, and more compatible with international standards for data sharing and reuse. Unlike some existing tools, LabFriend is based on open-source technologies and is being built to integrate with a range of open-source ELNs, including Herbie, which already support semantic data entry.
The project will deliver stand-alone software components that can be plugged into different ELNs. By simplifying and harmonizing how metadata is collected, LabFriend will help scientists produce more complete, accurate, and reusable datasets. This will have a major impact on the quality of research and its long-term value.
This project is a joint effort of two DLR institutes, Institute of Data Science and Institute of Frontier Materials on Earth and in Space, and two Hereon-Zentrum institutes, Institute of Membrane Research and Institute of Metallic Biomaterials working together on semantic technologies, speech processing and ELN integration. The consortium combines a diverse set of competencies and experience. DLR Institute of Data Science, with its experience in applying semantic technologies in diverse scientific environments, especially in laboratories, plays a unique role in the project, coordinating it and bridging specialists in different experimental domains. The project is funded in the frame of the Helmholtz Metadata Collaboration (HMC).
Project duration: 04/2025 - 03/2027