Data Sharing on the interplay between Research and Knowledge: Enhancing the Awareness of Open Science in daily research

The generation of new knowledge, the ultimate goal of any research effort,  is  mediated today and even more  so  in  the  future  through  the  collection and analysis of  large  amounts of  data. These research data sets represent  the  most important and lasting value of any research project.
 There is general  consensus on  the  importance of effective  data  quality  management  to  ensure the greatest  possible  benefit  for  science  and society from the ever-growing amount of research data.
The FAIR principles  of research  data management can be viewed  as  a  robust,  sustainable and easily conceivable  benchmark  for  data quality. Findability, accessibility, interoperability and reusability are also the prerequisites for open science,  as sharing data only makes  sense  if  the  shared  content  is easily interpretable  for  the recipient scientist.  Merging of data sets  from different projects and the creation of synergies   between  different  scientific   disciplines    also  depend  to  a  large  extent on the FAIRness of    the research data.  
Surplus knowledge from already  collected data can only be generated if there is con-sensus on the use of metadata  and terminology. Poster presented to the RDA Germany annual meeting, Potsdam 21./22.02.2024