Sound Data Management Training (SoDaMaT)¶

Overview¶

Sound Data Management Training (SoDaMaT) is an eight-month project to create and evaluate discipline-specific data management training material for digital music and audio research. The materials will be targeted to: postgraduate research students (MSc and PhD); research staff (postdoctoral researchers, CIs, PIs); and academic staff. The project is to run at the Centre for Digital Music (C4DM) at Queen Mary University of London (QMUL) from June 2012 to January 2013, in collaboration with the QMUL Learning Institute.

The immediate objectives of the SoDaMaT project are:

1. to develop specific training material on data management planning for research projects, targeting research and academic staff in digital music and audio research;
2. to develop training material covering the different aspects of research data management, including subject-specific topics such as music copyrights, for postgraduate students, research and academic staff in the area of digital music and audio;
3. to collaborate with institutional partners (QMUL Learning Institute), other projects (SoundSoftware.ac.uk), and discipline-specific societies (Digital Music Research Network, International Society for Music Information Retrieval) to test the training material in postgraduate courses, workshops, and tutorials, and to collect feedback on their quality and impact;
4. to collaborate with institutional partners (QMUL Learning Institute; EECS School of Electronic Engineering and Computer Science; QMUL IT Services) to embed the training material into postgraduate curricula and Continuous Professional Development courses to assure the long-term sustainability and generalisation of the project's results to other similar disciplines.

The requirements will be scoped, and the training materials will be trialled, within the Centre for Digital Music (C4DM), part of the School of Electronic Engineering and Computer Science (EECS) at Queen Mary University of London.

In addition to designing, producing, and evaluating discipline-specific training material, a wider objective is to promote good practice in research data management through education and awareness both within Queen Mary University of London, and across UK and overseas research institutions in the digital music and audio area.

Background¶

A survey on data management practices among researchers and students at C4DM, conducted during the JISC-funded "Sustainable Management of Digital Music Research Data" (SMDMRD) project, showed very low awareness of the importance of research data management as part of the research workflow. Although many researchers organise their data in folders and perform semi-regular backups, to the specific question "Do you have a particular strategy for data management", the majority responded negatively. Through our links with other groups via the EPSRC-funded Sound Software project (see Collaborations section), we have good reason to believe the situation is similar in many other music and audio research groups. The results of the survey point to the need for raising awareness of the benefits of research data management, such as a potential increase in citations, understanding and meeting data management requirements set by funding bodies (e.g. EPSRC), and producing sustainable and reproducible research.

The SMDMRD project defined a set of data management policies and created a pilot data management system for C4DM. This was a pioneering effort within QMUL, and a collaboration with the QMUL IT Services has been recently established to adapt the results of the SMDMRD project to define institutional policies, and build an institutional research data repository. Policies can be used to raise awareness among research staff and students by imposing rules of conduct, and adherence to such policies is supported by tools like a data repository. Nevertheless, policies only give a general idea of why research data management is important, and the enthusiasm for using a data management system can easily fade if a culture for data management is not established. These facts point to the need for continuous, embedded, sustainable data management training, with strong focus on promoting the benefits of research data management, ideally from the early stages of a researcher's career.