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Learning materials related research data management and data analysis   

Research data management guidelines

• Personal data workflow (see also How to handle personal data in research) 

Research data management quick guides

• (Please log in with your Google account to download)
• (Science-IT)
• (Science-IT)

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

• Bäckström, T. (2023). Privacy in Speech Technology. arXiv preprint .
• 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.