🤔 Researcher with interests in Semantic Web standards and open-source, working on AI for research software documentation.
📚️ Publications
🔬 Latest research projects
Can machines interpret and execute plans and instructions for research software installation? We present a method called READMEtoPLAN, which takes as input a the installation instructions and outputs a corresponding executable step.
Scientific open source Software (SOSS) - A repository that given an software arfefact DOI, it will computationally reproduce the software environment of the package.
A knowledge graph (KG) using semantic web technolgies. We defined requirements and improvements to make the most comprehensive database about historical games FAIR, with special attention as to whether the existing tools help enhance data published on the web in digital humanities.
A KG that integrates data sources from nutritional and food price sources using ISO-FOOD Ontology. The goal is to create a KG to monitor food price and analyse cost affordability of healthy habits over time.
The Community Data Driven Insight (CDDI) is a project that implemented FAIR research data and software management strategies with digital techniques across research communities.
Co-developed a web service to insert projects from the Institute of Data Science (IDS) and its information from git repositories, alongside with generating JSON file using DOAP schema.
In 2019, I joined the Institute of Data Science (IDS) to develop my research software engineering skills, learn more about digital technologies, and contribute to open science. As research data scientist, I've been also involved in EU-wide research projects that investigate models and methods for efficient semantic indexing, linking and retrival of heterogeneous and distributed data sources such as the European Open Science Cloud (EOSC), and EU COST Action CA19134 - Distributed Knowledge Graphs (DKG), as well as building communities and standards for research data management and software best practices. Previously, I had also worked in industry as data scientist on a project funded by the European Space Agency (ESA) and the European Investment Bank (EIB) related to data integration, visualisation and statistical analysis. Check all archived research projects in this Github repository (@carlosug) or on this 🗂️ PDF.
🎭 Teaching and supervising
Introduction to software best practices for researchers of TU Delft University.
Training and e-Infrastructure for Research Software Development at TU Delft University.
Introduction to data science with Python/Pandas/Seaborn for undergraduate students of social science (2022, 2021 and 2020).
Data science in R for bachelor students in the applied data science minor.
I am an official Instructor in The Carpentries Open Science Community (Instructor certificate) and co-supervised three BSc/MSc student projects related to semantic technologies and network science.
🛠️ Technical skills
The displayed scores are obviously subjective, please refer to my 🗂️ CV for a better account of how those skills were used.
Python
4/5
RDF
3/5
SPARQL
3/5
Ontologies
3/5
SHACL
3/5
Bash
2/5
Linux
3/5
Docker
1/5
Git
3/5
OpenAPI
1/5
RDFLib
3/5
TypeScript
2/5
React
2/5
Material UI
12/5
HTML/CSS
3/5
ShEx
2/5
RML
2/5
Protégé
1/5
Rstudio
4/5
Jupyter
4/5
Node.js
2/5
Express.js
2/5
D3.js Graph
2/5
NetworkX
4/5
RDF4J
2/5
MongoDB
1/5
SQL
2/5
NLP
3/5
GraphQL
1/5
Pandas
4/5
Gatsby
2/5
MacOS
4/5
💬 About me
Hello! I'm Carlos, and I am one of those human beings who loves to learn from others, science and research.
I am a Trainer & Educational Developer for the Research Data and Software Team (RDS) at TU Delft Library , and I'm doing a PhD in the Ontology Engineering Group at the UPM. I am a strong advocate of Open science and my research interests involve the usage of semantic web standards, and software open source in general.
When not dealing with numbers or reading, I’m a happy uncle, a swimmer, a tennis player and, last but not least, a loving supporter of Real Zaragoza football team.