Daniel Garijo Verdejo is a Distinguished Researcher at the Ontology Engineering Group of the Universidad Politécnica de Madrid, currently holding a Beatriz Galindo Award (2021-2025). Previously, he held a  research Computer Scientist position at the Information Sciences Institute of the University of Southern California, in Los Angeles, where he also had postdoctoral position between 2016 and 2018.

Daniel graduated from his PhD on Artificial intelligence (extraordinary award, 2015) at the Ontology Engineering Group of the Polytechnic University of Madrid. His PhD (2011-2015) was funded by a FPU scholarship of the Spanish government (2011). During this time, he completed three internships at the Information Sciences Institute that shaped his line of research and fostered his collaborations with researchers from other institutions in the US. Back in Spain, Daniel also collaborated with European project partners from the UK and Germany that boosted the international visibility of his work. In addition, Daniel has participated in community initiatives such as W3C standardization processes (e.g., Provenance Incubator Group, Provenance Working Group) and the Dublin Core Metadata Initiative.

Daniel’s line of research focuses on the area of e-Science, in particular on capturing the context and metadata of scientific software and computational experiments to foster their (re)usability. In order to do so, all the elements belonging to an experiment are converted to Knowledge Graphs and exposed as Linked Data. Important contributions derive from this line of research:

1) Generation of semantic models and contribution to standards to represent the metadata and context of all resources (data, software and methods) associated with a scientific research experiment

2) Methodologies and frameworks for detecting commonalities among scientific experiments and fostering their reusability.

3) Frameworks for automatically capturing, exploiting and publishing scientific software metadata and its associated results.

4) Means to improve the explainability of experiments by automatically creating narratives of their results

As a result of his work and international visibility, Daniel has published in top conferences of his area of research (International Conference of the Association for the Advancement of Artificial Intelligence (AAAI), International Semantic Web Conference (ISWC), International Conference on Intelligent User Interfaces (IUI), International Conference on eScience, etc.) and has been an invited speaker at universities all over the world (Stanford, Hawaii, Austin, Amsterdam, London, etc.). In addition, he has been invited to three different Dagstuhl seminars (on provenance, reproducibility and scientific software respectively) to discuss about the future of a research topic/area.

Daniel has collaborated with researchers from multiple disciplines, ranging from Astronomy to Geosciences, and supervised over 25 undergraduate, graduate and master students that have worked under him in national and international projects.

Daniel has also been heavily involved with the scientific community, having organized workshops for scientific knowledge capture (International workshop on Capturing Scientific Knowledge (SciKnow), International Workshop on Enabling Open Semantic Science (SemSci2018)) and reproducible AI (AAAI 2020 Workshop on Reproducible AI - RAI2020) at the top conferences o