Research languages from different domains of science have distinct needs and means of expression. However, when transferring knowledge between researchers with different backgrounds, information often gets lost in translation. Therefore, the research data management (RDM) arises from the necessity to standardize suitable practices on all steps of the data lifecycle. This presentation reflects my lessons as 1) a researcher, with the responsibility of setting up a data management plan (DMP) within my group, and 2) as a Data Agent at Aalto University (Finland). I start by describing the basic DMP methodology intended for general use of a multidisciplinary group: a) introduction to RDM by using some practical and relatable challenges that a researcher can face during the handling of data; b) description of the plan for data produced by the group. The DMP required to be simple enough to be easily remembered and without interfering too much with personal preferences. In a latter part of the presentation, I describe the operation of the Data Agents service. The Data Agents network of Aalto University relies on researchers engaged to improve data management practices distributed over different departments. Therefore, knowledge on the RDM best practices is founded in active cooperation within the network, spread over the campus through personalized guidance and education services.[1] (1) Darst, R.; Glerean, E.; H ̈aggman, D.; Icheln, C.; Jalava, M.; Kuklin, M.; Nieminen, K.; Pawlicka-Deger, U.; Safdar, M.; L ̈ahteenm ̈aki, I.; S ̈oderholm, M.; Sunikka, A.; Bingham, E. 2019, Publisher: Zenodo Version Number: 1.0, DOI: 10.5281/ZENODO.3514961.