Demonstrator Market (walk-in)
Today’s global challenges can benefit from digital solutions. Join us in inspiring fellow WUR researchers to make better use of digital tools and technologies. Demonstrators can range from software that give easy access to research results to algorithms based on sophisticated machine learning, or any other digital creations.
Colleagues from all over WUR will be invited to visit the market. Send an email to firstname.lastname@example.org to register.
Automated data management for survey data processing in consumer research
The consumer data platform delivers tooling for creating survey designs that makes FAIR data management easy. Consumer researchers start with selecting harmonised measures to create a survey design in a matter of clicks. When the consumer researcher finishes the survey design, a data model is automatically generated in the background. This data model is used to validate datasets that will be gathered based on the survey design. As a consequence, the data set will comply with FAIR data management principles, unburdening the researcher of complicated data management tasks.
- FAIR Data Station for the Life Sciences
The FAIR Data Station, a metadata ingestion platform that helps the researcher to improve the quality and safeguards the machine-actionability of experiment metadata. In brief, data FAIRification the easy way! The standalone application is written in java and makes use of Semantic Web technologies thereby allowing users to build their own repository of FAIR experiments.
- Wageningen modelling toolbox demonstrator
The Wageningen Modelling Group has developed several tools that support working with models. In this demonstrator we will showcase a number of them, a.o. the model gallery, the good modelling practice wiki and the quality assessment tools.
- Numerical model for designing and predicting the passive modified food packaging
The tool describes the mass transfers of gases (O2/CO2/N2) in the passive modified food packaging and spatial diffusion of O2/CO2 in the food sample. The passive term means without chemical reactions in the packaging (i.e. the lid film and the tray). The tool requires the input parameters from users: the system's size, the permeability of the O2/CO2/N2 in the packaging; O2/CO2 solubilities at the headspace-food interface and O2/CO2 diffusivities in the food sample and a storage temperature. This tool then numerically predicts the % O2/CO2/N2 in the headspace over time (This helps to simulate the shelf life of the food at different storage temperatures). If the users would like to product/ design the packaging to reach the targeted profiles of O2/CO2/N2 in the headspace at the steady state, the tool is also able to propose the values of permeabilities of O2/CO2/N2 in the packaging by optimizing with the targeted profiles.
- MCRA: Web platform for chemical exposure, hazard and risk assessment
On a daily basis, people are exposed to multiple chemicals via food intake, inhalation and dermal contact. The risk to human health resulting from this exposure depends on the effects of the different chemicals in the mixture and how they combine. MCRA stands for Monte Carlo Risk Assessment. It is a web-based platform containing various models that users can use to assess these health risks for specific populations in various scenarios.
- WR Model Gallery
The Model Gallery helps you to find clients, and clients to find you, for application and development of your model.
- Digital sugar reduction tool for product reformulation
Replacement of sugar is a challenging task as sugars do not only provide sweetness, but also play a crucial role in the structure and texture of food products. By identifying and combining different ingredients, an optimal mixture can be found that allows sufficient sugar reduction without compromising on texture and taste. We have developed an innovative digital reformulation tool in which we have implemented knowledge about the physical and chemical principles that control sugar functionality. With the use of algorithms optimal sugar replacers for specific formulations are identified, which allows for tailor-made solutions depending on specific bakery reformulation goals.
- ScienceBox: The Data Science Platform of CERN deployed at WUR
ScienceBox is developed at CERN (European Organization for Nuclear Research) and is a collection of applications which deliver a complete toolchain for DS/AI. It consists of a shared storage system for large datasets, and a Jupyter notebook based web interface for running code in programming languages such as C++, Python, R and Octave. All the most popular packages are preinstalled. ScienceBox is a server-based system, accessible via the browser, and thus requires no setup time for end-users.
- TALK (Team Associations for Linking Knowledge) Tool
Given the diversity of experts and stakeholders in research areas such as Food Systems, it is crucial to develop a shared language. The aim of project is to create support for researchers from different backgrounds to discuss terminology and in this way get a shared understanding and alignment in a multi or interdisciplinary project in a joyful way-such as a game.
- Solving computation challenges in crop monitoring and yield forecasting
We coupled a java implementation of the WOFOST model with Apache/Spark allowing distributed computing of crop simulations with WOFOST. Our results demonstrated that a large task such as rerunning the archive for a crop/region (e.g. winter-wheat over Europe) which could take a day, could be reduced to 7.5 minutes.
- WANDER - Advancing Research & Education through XR
Explore & Discover the most advanced 3D visualisation and immersive techniques such as AR & VR and how they can be applied in the research & education field. We will be showcasing several examples designed and developed by WANDER at WUR.
- Continuous welfare monitoring in production animals using tracking and computer vision technologies
Animal welfare is one of the pillars for sustainable livestock production. Animal behaviour can be used as welfare indicator. The assessment of behaviour is primarily done by veterinarians or farmers and is, consequently, limited by time and space. This means that we have snapshots of subjective information available over time. Innovative technologies, like tracking and computer vision, open opportunities to assess existing and new behavioural traits and to monitor these continuously in group-housed animals. Here at WLR we work on developing new scalable algorithms to assess behavioural traits using innovative technologies and link these to animal welfare.