Handbooks and methodological works

This page collects the guidelines and handbooks co-authored by the Data Agents and the Research Data Management Network. Also selected works by Aalto University researchers with a focus on methodologies, research data and open science are listed. All materials are available open access for any interested reader.

Works by Aalto researchers that focus on methodologies, research data and open science 

  • Bäckström, T. (2023). Privacy in Speech Technology. arXiv preprint arXiv:2305.05227
  • Hasanzadeh, K., Kajosaari, A., Häggman, D., & Kyttä, M. (2020). A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality. Computers, Environment and Urban Systems, 83, Article 101513. 
  • Himanen, L., Geurts, A., Foster, A. S., & Rinke, P. (2019). Data-Driven Materials Science: Status, Challenges, and Perspectives. Advanced Science, 6(21), Article 1900808.  
  • Hämäläinen, P., Tavast, M., & Kunnari, A. (2023). Evaluating Large Language Models in Generating Synthetic HCI Research Data: a Case Study. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23) Article 433 ACM. 
  • Pauw, B. R., Smales, G. J., Anker, A. S., ... & Wuttke, J. (2023). The human factor: results of a small-angle scattering data analysis round robin. Journal of Applied Crystallography. 56, 1618-1629. 
  • Räisä, O., Jälkö, J., Kaski, S., & Honkela, A. (2023). Noise-Aware Statistical Inference with Differentially Private Synthetic Data. In F. Ruiz, J. Dy, & J-W. van de Meent (Eds.), Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023 (pp. 3620-3643). (Proceedings of Machine Learning Research; Vol. 206). JMLR.  
  • Salami, D., Streibel, O., Rhenius, M., & Sigg, S. (2021). A FAIR Extension for the MQTT Protocol. In Proceedings of 16th International Conference on Mobility, Sensing and Networking (MSN 2020) (pp. 10-16). Article 9394261 IEEE.; 
  • Vicente-Saez, R., Gustafsson, R., & Van den Brande, L. (2020). The dawn of an open exploration era: Emergent principles and practices of open science and innovation of university research teams in a digital world. Technological Forecasting and Social Change, 156, Article 120037. 
  • Wahid, K. A., Glerean, E., Sahlsten, J., Jaskari, J., Kaski, K., Naser, M. A., He, R., Mohamed, A. S. R., & Fuller, C. D. (2022). Artificial Intelligence for Radiation Oncology Applications Using Public Datasets. Seminars in Radiation Oncology, 32(4), 400-414.  

Links to research data management instructions

Follow these links to navigate through research data management instructions.

People talking with each other

Research Data Management (RDM) and Open Science

Properly managed research data creates competitive edge and is an important part of a high-quality research process. Here you will find links to support, services and instructions for research data management.

RDM & Open Science Training

Training in Research Data Management and Open Science

We offer free and open to all training in research data management and open science.

Generic computational workstation, Photo by Aalto University / Marijn van Vliet

Research Software Engineers

Aalto RSE provide specialist support in research software development, data, and computing

Harald Herlin

Aalto Data Hub (external link)

Explore research data and data-oriented services available at Aalto University

light spirals

Aalto Materials Digitalization Platform - AMAD

Materials data infrastructure for Aalto University

This service is provided by:

Research and Innovation Services

Did you find what you were looking for? If not, please contact us.
  • Published:
  • Updated: