RDMF13: notes from breakout group 3 (roles and training)

This breakout session brought together over 30 attendees across the two sessions to discuss roles and (staff and student) training for preparing data - and other research objects - for deposit. It was chaired by Sophie Salffner of SOAS.
Following a brief introduction from Sophie on the institutional roles and activities at SOAS, the group were asked to share experiences from their own organisations.  

Roles:

• A number of organisations have developed, or are developing, new dedicated roles to support data management.
• Whatever the size of an organisation, successful data management involves close collaboration across a variety of roles and departments (e.g. researcher, library, research office, IT).
• Staff roles ranged from “one-man / one-woman bands” – where an individual performs multiple activities in relation to data management – through to more complex structures and services.
• Where RDM infrastructure is fragmented across an institution it is important to have someone who can bring all stakeholders together to make sure that activity within the organisation is connected.
• A ‘partnership’ approach to RDM services was discussed for smaller universities. Universities in a regional area might work together to share responsibility for services e.g. University A would be responsible for humanities queries, University B would be responsible for science etc.   
• It was noted that sometimes it is necessary to ‘stoke up’ demand from researchers to help articulate a need for additional data roles and services.

Training:

• Training needs differ - it’s important to understand your audience and tailor training sessions accordingly. Even generic sessions need to be ‘badged’ for their specific audience to make them more meaningful.
• Where possible, tap into local networks of expertise. Are there any particular departments or schools with good research data practice? Is it possible to forge links?  
• Some researchers are more receptive to data management training than others. Some organisations deliberately target PhD students and Early Career Researchers to try and embed good practice early. Data management is sometimes made a compulsory component of PhD training.
• A central point of contact (e.g. shared email, helpdesk, website etc.) was recommended to make sure work is aligned and queries are sent to the most appropriate department.
• The Research Office are important stakeholders – they are often seen as ‘trusted partners’ in in the research process and have a ‘channel’ into researchers. Researchers often have to engage with the Research Office at the start of a new research project and it’s important to consider issues around data management training then.   
• In many organisations, academic liaison librarians are being ‘upskilled’ to deliver training.  However, there are concerns that liaison roles are already full and many librarians are too busy. Some librarians are also worried about their credibility when talking to researchers about data (‘What does the Library know about MY research data’?) One participant reported that the word ‘library’ was deliberately left off marketing materials for data training events - even though the library was leading on training.  
• As well recommending data management courses (e.g. MANTRA etc.), many organisations are developing new online web pages / information to help train their researchers. User case-studies are also being produced to help raise RDM awareness across the university.
• Important to speak the same language: essential that RDM staff are using the same vocabularies as researchers to ensure that there is common understanding.  
• It was agreed across the group that we’re playing a “long game” with RDM training and that culture change takes time. While we can hope to see some quick results it may take a generation to change attitudes and motivations towards data sharing.  

To paraphrase a remark made at the end of the day – it is only by establishing a ‘village’ of data management experts that institutions can successfully serve their researchers’ needs. While data management support may vary, this breakout session demonstrated that institutions are furthering activities around roles, training and infrastructure to help establish this ‘village’ and meet the challenges of data management.