In recent years, we witnessed an increasing number of funding agencies, scientific journals and scientists agreeing that society and science benefit from open access to research data. Benefits derive mainly from increased access to knowledge for all and improved transparency and credibility in academia. However, despite the advances in open science and open data, three significant aspects still need considerable policing: data quality, the accompanying summaries with basic information of the data files (i.e. metadata) and computational codes used to generate the research outcomes. Only by having these three components together, we can achieve efficient data sharing and reuse, and hence higher transparency. Here, we present two complementary approaches that potentially can help with shared data quality: (i) data file(s) sharing should be guided step-by-step in public archives with mandatory metadata, and (ii) journals creating assistant data editor positions at editorial boards with a leading role in data quality and computational reproducibility. Forty-four editors-in-chief in the field of behaviour, ecology and evolution shared their opinion with us regarding these two approaches. Although most of the views were divided, the majority estimated that their current editorial board members do not have the necessary skills to assess the quality of shared data. Since data are the core of research studies, we should consider not only data presence but also quality as a requirement for publication.