The best thing about working in research data management is that you get to meet and work with amazing researchers.
This might seem really obvious but it's amazing how much of the focus in this area sometimes seems to be on the technology (data capture solutions, repositories, metadata stores) and on data and metadata as bits of content that need to be managed, rather than people! Yes, well-managed research data helps with compliance and research impact, but one of the most important reasons to do it is because it can make a research team's day-to-day life easier and make their conduct of research - in an office, in a lab, or in the field - more efficient and effective.
This afternoon I am going with a colleague to do some data planning with a research group in Griffith's Centre for Health Practice Innovation. The research team, led by Professor Wendy Moyle, is doing amazing research funded by the National Health and Medical Research Council. They are investigating the use of therapeutic robots in the care of older people and people with dementia. The robot being used in this clinical trial is called PARO and it takes the form of a baby harp seal!
The PARO robotic seal. Credit: tsukabajin on Flickr. Licence: CC BY-NC-SA 2.0. |
Our work suggests that PARO has the potential to positively influence the lives of people with dementia, but further research is required to understand its effect. We need to know whether the benefits are seen when PARO is trialled with more people and the ideal length of time that people with dementia should spend with PARO. Given the high cost of purchasing ($AU5,000) and maintaining these robots, which currently have to be returned to Japan for maintenance, we also need to conduct a cost-benefit analysis. It is imperative that residential aged care facilities do not purchase robots without understanding how to use them, which residents are most likely to benefit and the best strategies for introducing and removing robots from residents.Here's a video about Prof Moyle and her work:
Prof Moyle's team have some serious data management challenges. They are looking to recruit hundreds of participants and will be generating a large volume of data in the form of sensor data from wearable devices as well as observational videos. Each video file could be 2-3GB and will need to be high-resolution to facilitate automated data analysis. The data collection process will take place off-campus and there will be a need to transfer data from SD cards in video cameras to secure university storage systems. Collaborators in the research come from different organisations, and will need secure access from their own organisations in order to perform the required analysis. Given the nature of the research and its participants, ethical concerns are also paramount.
This example is not unusual. As digital data collection methods improve and collaboration becomes the norm, research data management becomes ever more complex. I feel very privileged to be able to partner with researchers and to use my information management skills and knowledge to contribute in a small way to such amazing work.