Run My Code

RunMyCode enables scientists

to openly share the code and data that underlie their research publications

This service is based on the innovative concept of a companion
website associated with a scientific publication.

Users

Users can access the code and data used by researchers.
Researchers

Researchers can share the code and data used in a scientific paper. This increases transparency and reproducibility.
Journals

Journals' editors can invite the authors who publish in their journals to share their code and data on RunMyCode.

Companion websites

Too Much of a Good Thing?

International Journal of Research in Marketing (2019)

Gaustad Tarje, M. Bendik, Warlop Luk, and Fitzsimons Gavan J.

Evaluating marketplace synergies of ingredient brand alliances

International Journal of Research in Marketing (2018)

Bowman Douglas

Dataset for agent-based model of interactions between air pollutants and greenery using a case study of Yerevan, Armenia

Data in Brief (2019)

Akopov Andranik, Beklaryan Levon, and Beklaryan Gayane

Smart Systemic-Risk Scores

Working Paper (2018)

Benoit Sylvain

The lateral growth and coalesence of magma systems

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A (2019)

Biggs Juliet and Annen Catherine

Shaping Consumer Preference Using Alignable Attributes: The Roles of Regulatory Orientation and Construal Level

International Journal of Research in Marketing (2018)

Sun Jin, Keh Hean Tat, and Lee Angela Y.

Backtesting Expected Shortfall via Multi-Quantile Regression

Working Paper (2018)

Couperier Ophélie and Leymarie Jérémy

Selection of weightages for causative factors used in preparation of landslide susceptibility zonation (LSZ)

Geomatics, Natural Hazards and Risk (2018)

Gupta Sharad Kumar, Shuka Dericks P., and Thakur Manoj

Cross-Gramian-Based Dominant Subspaces

Working Paper (2018)

Benner Peter and Himpe Christian