Awesome Utrecht University

A curated list of awesome research code, software, manuals, and more on Git, developed by Utrecht University researchers, students, and employees. The list can be your starting point to find interesting UU projects, and get inpired and learn from other projects. Is your project also "awesome"? Add it to this list (see Contributing).

"The purpose of this list is to have a collection of projects using Git version control, that score high on openness, reusability, and transparency in order to showcase good examples of open practices. In the context of this, awesome refers to projects that showcase the FAIR (findability, accessibility, interoperability, and reusability) and Open Science spirit. This is for example shown in repositories that have a license that permits reuse and a README file with clear documentation.

In order to promote open science, Utrecht University has introduced the Open Science Programme. Beside topics like Open access, Public engagement, and Recognition and rewards, there is a strong focus on FAIR Data and Software. This awesome list was created by efforts of the track of FAIR Data and Software to help researchers to find good examples. We believe that learning by example is very useful in the field of Open Science and FAIR Data and Software."

FAIR Data and Software team

❣️ We are looking for Utrecht University researchers that are interested in helping to maintain this list. Please reach out if you would like to assist (see Contact)!

Awesome Utrecht University

Projects

Research code

Research projects with supplementing code stored on online Git repositories.

Aragonite_clumped - R code for processing and plotting of clumped isotope data from aragonite samples in "Temperature dependence of clumped isotopes (∆47) in aragonite"
ContrastiveExplanation - Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
DA_model - R code for simulating diffusion-advection models for leaching of trace elements into tooth enamel during burial and diagenesis of archeological and paleontological specimens in "High-resolution trace element distributions and models of trace element diffusion in enamel of Late Neolithic/Early Chalcolithic human molars from the Rioja Alavesa region (north-central Spain) help to separate biogenic from diagenetic trends"
GeoNewsMiner The GeoNewsMiner (GNM): An interactive spatial humanities tool to visualize geographical references in historical newspapers
PCR-GLOBWB_model - PCR-GLOBWB (PCRaster Global Water Balance) is a large-scale hydrological model intended for global to regional studies and developed at the Department of Physical Geography.
PuReGoMe - Notebooks of the PuReGoMe Project of the Netherlands eScience Center and Utrecht University.
Saliency-Tubes-Visual-Explanations-for-Spatio-Temporal-Convolutions - Implementation of Saliency Tubes for 3D Convolutions in Pytoch and Keras to localise the focus spatio-temporal regions of 3D CNNs.
seasonalclumped - R package for generating virtual stable isotope data to model sampling strategies for seasonality reconstructions in "Optimizing sampling strategies in high-resolution paleoclimate records"
SoftPool - Code for approximated exponential maximum pooling.
Squeeze-and-Recursion-Temporal-Gates - Code for : [Pattern Recognit. Lett. 2020] "Learn to cycle: Time-consistent feature discovery for action recognition" and [arXiv] "Right on Time: Multi-Temporal Convolutions for Human Action Recognition in Videos".
stdstats - Simulation and plotting code for "Optimizing the use of carbonate standards to minimize uncertainties in clumped isotope data"

Research software

Software developed by researchers and employees of Utrecht University. The software in this list is installable and can be used in new or existing research projects or courses.

asreview - Active learning for systematic reviews
bain - Bayes Factors for Informative Hypotheses
mice - Multivariate Imputation by Chained Equations
- ggmice - Visualize incomplete and imputed data with the R package ggmice
oceanexplorer - An R interface to the NOAA World Ocean Atlas
osmenrich - Enrich sf data with geographic features from OpenStreetMaps.
parcels - Main code for Parcels (Probably A Really Computationally Efficient Lagrangian Simulator)
pcraster - Environmental modeling software
pdb-tools - A dependency-free cross-platform swiss army knife for PDB files.
recordlinkage - A toolkit for record linkage and duplicate detection in Python
Ricgraph - With Ricgraph, you can create a graph from research information that is stored in various source systems. You can explore this graph and discover relations you were not aware of. For code, extensive documentation and videos follow the link.
ShellChron - R package for constructing age models based on stable oxygen isotope records from accretionary carbonate archives
Stitch - A program for de novo sequencing of antibodies/proteins based on massspectrometry data.
text_explainability - A generic explainability architecture for explaining text machine learning models.
text_sensitivity - Extension of text_explainability for sensitivity testing (robustness, fairness).

Research data

Research data stored in git repositories.

childdevdata - R package with Child Development Data from ten studies, containing 1,116,061 assessments made on 10,831 unique children during 28,465 visits, covering 21 different instruments.
CoronaWatchNL - Numbers concerning COVID-19 disease cases in The Netherlands by RIVM, LCPS, NICE, ECML, and Rijksoverheid.

Research project management

Tools for research project management, data management, software management, and lab tools.

labphew - a minimalist functioning code module and folder structure, built to teach and exercise with computer-controlled measurements using Python.
worcs - Rstudio project template and convenience functions for the Workflow for Open Reproducible Code in Science (WORCS)

Education and workshops

Open teaching materials are guidelines, tutorials or any other educational material. Where to discover further resources relevant for UU research like books, podcasts, additional websites and newsletters.

DarwinCAT A Shiny web application to experiment and visualize how evolution is distorted by the geological record. Useful in teaching palaeobiology and evolutionary biology. Developed and used in courses at the Department of Earth Sciences, Utrecht University.
Shellbed Condensator A Shiny web app to visualize the effects of changing sedimentation rates on the formation of fossil accumulations. Useful in teaching geoscience and palaeobiology. Developed and used in courses at the Department of Earth Sciences, Utrecht University.
ShinyEducation The 'ShinyEducation' project at Utrecht University's Department of Methodology & Statistics uses interactive Shiny applications to explain statistical concepts. Applications cover topics like ANOVA, ANCOVA, t-tests, and correlation. This hands-on approach promotes immersive learning. Explore more here.
Textbook on Quantitative Methods and Statistics Textbook on Quantitative Methods and Statistics aimed at humanities researchers and students (English version, EN) (Dutch version, NL)
workshop-introduction-to-R-and-data - Material for the workshop 'Introduction to R & data' by RDM Support

Collaboration groups

Collaboration Groups are organizations with many involved parties.

CLARIAH - CLARIAH offers humanities scholars a Common Lab providing access to large collections of digital resources and innovative tools for research
stan - Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation. Thousands of users rely on Stan for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.

Add project to this list

Do you know about a project that should be in the Awesome Utrecht University list? This could be your own project or a project of one of your colleagues. We would love to hear about that project! The contribution guidelines help you to propose a new project to the list.

Background

What is an Awesome list?

"Awesome lists" are curated lists of awesome stuff. The lists are very popular in the field of open source development (see https://github.com/sindresorhus/awesome). Read "The awesome manifesto" for more information about awesome lists.

Initial project collection

The initial collection of projects was made based on the collected repositories from the SWORDS-UU project (more information follows soon). Repositories were considered when they have a license and 25 stars or fulfill 4/5 FAIR criteria.

Implementing Awesome lists for your university

We encourage other universities to also implement awesome lists for their research. You can fork this repository as a starting point. Having such a list is a useful resource to showcase good projects that have been conducted or are still ongoing and helps promoting the open science approach. If you need help getting started please don't hesitate to reach out to us. We will gladly assist you.

Contact

This awesome list was created by efforts of the FAIR Data and Software team of Utrecht University. If you have any question or remark about this list, do not hesitate to contact any of the current maintainers via mail:

or open an issue on GitHub.

Are you a Utrecht University researcher looking for support on making your research code and data open and FAIR? Or do you want to brainstorm about these topics? Feel free to contact RDM Support.

Ricgraph

What is your project about?
With Ricgraph (https://github.com/UtrechtUniversity/ricgraph), you can create a graph from research information that is stored in various source systems. You can explore this graph and discover relations you were not aware of. We have developed Ricgraph (Research in context graph) because our university had a need to be able to show our researchers, their skills, suborganizations (e.g. faculties, departments), projects and research outputs (e.g. publications, datasets, software packages) in relation to each other. This information is stored in different systems, such as Pure, OpenAlex, Yoda, the Research Software Directory, and our organization’s employee pages.

Why do you think your project is a great addition?
What if… we look at research information as a graph? We would have relations between objects, we would be able to “walk” from one object to another, and related objects would be neighbors. For example, starting with a researcher, this person’s publications are only one step away by following one edge, and other contributors to that publication are again one step (edge) away.

With Ricgraph, you can create a graph from research information that is stored in various source systems. You can explore this graph and discover relations you were not aware of. We have developed Ricgraph (Research in context graph) because our university had a need to be able to show our researchers, their skills, suborganizations (e.g. faculties, departments), projects and research outputs (e.g. publications, datasets, software packages) in relation to each other. This information is stored in different systems, such as Pure, OpenAlex, Yoda, the Research Software Directory, and our organization’s employee pages.

By combining this information in one graph, it is possible to show research in context (hence the name). Ricgraph is a graph that uses nodes and edges to represent objects and their relations. It can be used to store, manipulate and read metadata of any object that has a relation to another object.

Ricgraph can answer questions like:

Which researcher has contributed to which publication, dataset, software package, project, etc.?
Given e.g. a dataset, software package, or project, who has contributed to it?
What identifiers does a researcher have (e.g. ORCID, ISNI, organization employee ID, email address)?
What skills does a researcher have?
Show a network of researchers who have worked together?
Which organizations have worked together?-

With Ricgraph, you can get metadata from objects from any source system you’d like. You run the harvest script for that system, and data will be imported in Ricgraph and will be combined automatically with data which is already there. Ricgraph provides harvest scripts for the systems mentioned above. Scripts for other sources can be written easily.

Ricgraph is open source software and can be found on GitHub (https://github.com/UtrechtUniversity/ricgraph).

Does your project fit into a category or do you want to suggest a new one?
I think a new category may be necessary, e.g. "General software" or "Graph software". Please feel free to add this software to any category you see fit.

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