About

The OpenScienceLab research group at Universidad Carlos III de Madrid is dedicated to meta-research for open science; evaluating scientific practices, designing policies, and training researchers to promote transparency, quality, and collaboration in scientific research. Its objective is to drive a positive change in the scientific community and contribute to the advancement of knowledge by implementing ethical, reproducible, and accessible practices.

The research group stands out for its interdisciplinary approach, which spans various scientific fields and focuses on the comprehensive analysis of the research cycle and its outcomes. To achieve this, it combines traditional methods of quantitative science studies, informetrics and research evaluation with practices and resources from disciplines such as psychology, cognitive neuroscience, history of science, ethics, forensic scientometrics, and data science, among others.

This approach allows for a deeper examination and understanding of policies and regulations surrounding open access, technological infrastructures for scientific data sharing, quality standards, and scientific dissemination processes, as well as critical evaluation of scientific practice and research ethics.

Research areas

Vocabularies and metadata for open science.
Research data infrastructures. Visibility and impact of research results.
Data management and sharing (Open data / FAIR data / Data sharing).
Reproducibility/replicability of science.
Citizen participation and citizen science.
Measurement and monitoring of Open access and Open data.
New forms of scientific communication/dissemination.
Questionable research and editing practices (QRP / QPP).
Science communication and data journalism.
Legal and ethical aspects of research (IPR, Data protection, etc.).
Innovation and valorization of knowledge produced by research.
New metrics (Next Generation Metrics) and alternative metrics.
Impact of open knowledge on institutions.
New professions in research management (Data stewards).
Multi, cross, inter, and transdisciplinarity in research.
Informetrics, scientometrics, bibliometrics, altmetrics and research evaluation.

Metascience and cross-disciplinary training require scientists with experience in conducting empirical research and a solid command of the details across multiple fields of expertise.

Maruyama, M., Beals, K.L., Bharati, A., Fuchs, H., Gardner, P.M., Guilmet, G.M., Hahn, R.A., Kamau, L.J., Kronenfeld, D., Kursh, C.O., Meeker, J.W., Pribram, K.H., Quiatt, D.D., Richardson, M., Rogers, M.B., Romanucci‐Ross, L., & van Esterik, P. (1980). Mindscapes and Science Theories [and Comments and Reply]. Current Anthropology, 21, 589 – 608.