Reflections on the MQ Datamind Workshop and Convention by an Early Profession Researcher


Mao Fong Lim, NIHR Educational Medical Fellow, shares their experiences attending September’s Information Science assembly and workshop.

We started with an surprising scene for an information science workshop on psychological well being – the workplace of Deutsche Financial institution in Central London. This was adopted by an equally shocking line from Marcos del Pozo Banos: “I don’t know how you can write code in R or Python”. 

This was each amusing and candid, however as I progressively found by the course of the workshop – very real looking. 

A bit about myself – I’m an NIHR Educational Medical Fellow in Psychiatry. Nonetheless, I contemplate myself a very early profession researcher (ECR), particularly in information science. My analysis goals to discover the immunological relationship between bodily and psychological well being. In doing so, I’m turning to massive information for solutions and climbing the steep studying curve that accompanies this pursuit.

I’ve all the time discovered programming extraordinarily daunting. I attended the MQ Datamind workshop to kickstart my foray into information science. Though teachers and informaticians made up many of the viewers, Marcos made it accessible. He launched programming as primarily the duty of speaking with a pc in numbers. 

I discovered Marcos’ worksheet/train on Kaggle to be an actual perception right into a programmer’s thoughts and a useful useful resource to return to sooner or later. The entire course of was damaged down into small steps, interspersed with statements: “now I’ll seek for related code on the web”. A number of researchers I’ve spoken to since have confirmed that that is, certainly, how they code in R! 

However in fact – information science is extra than simply crunching numbers and writing (or in search of code). Even on the workshop day, we have been launched to some implausible examples of how NHS scientific care and analysis could possibly be reworked by embedding processes, folks, and experience into current processes (Johnny Downs and Pauline Whelan).

The convention the following day provided much more insights into information science. Greg Farber from the NIMH posed a number of important questions concerning the interoperability of the info we acquire and efforts round coordinating this. This was additional echoed by the Psychological Well being Funders panel (Wellcome Belief, MQ, NIHR), which mentioned the concerted efforts of funding our bodies in facilitating information interoperability and numerous information science initiatives such because the Wellcome Information Prize. As an ECR, it was significantly fascinating to realize perception into the decision-making strategy of funding our bodies and the (typically dreaded) strategy of grant and fellowship functions. 

Andrew Morris of Well being Information Analysis UK (HDR UK) then gave an inspiring perception into the info science infrastructure obtainable within the UK. Linking again to earlier themes of information interoperability, we have been launched to the influence that HDR UK has had on healthcare, significantly in COVID-19, by offering huge datasets that enabled ground-breaking analysis.

We have been then launched to how information is collected by the implausible examples of MindKind (Mina Fazel) and the GLAD Research (Thalia Eley). MindKind was an amazing instance of coproduction, involving younger folks in how and what information is collected and the way that information is used. Each MindKind and GLAD have been stellar examples of how you can harness the attain of social media whereas being conscious of the pitfalls, such because the potential skewing of recruitment.  

I discovered it fascinating to see so many functions of information science in psychological well being. Specific highlights for me have been: 

  • Linking social care and well being information (DWP, kids in care)
  • Danger prediction fashions for psychological well being outcomes (Emmanuele Osimo, Ben Perry)
  • Properly-designed posters and presentation kinds of fellow researchers. (Particular point out to Max Taquet for a really slick and accessible presentation on his findings round COVID-19 mind fog).

Lastly, I left with an necessary reminder that beneath the veneer of (largely) agnostic information – are actual lives. As Ann John stated whereas introducing John Niven, we should do not forget that in information science, we’re utilizing public cash and information entrusted to us by actual individuals who have actual lives that shall be impacted by the findings and implementation of our analysis. John gifted us with an evocative, sincere and heartbreaking account of his brother’s loss of life by suicide over a decade in the past, which caused tears and a minimum of one standing ovation.

Total, it was a implausible workshop and convention that far exceeded my expectations and one which I might extremely suggest to fellow ECRs. On a private word, I’ve now acquired a big dataset that I’ll work on as a part of my first undertaking. I’ll take up a course on Mendelian Randomisation, which is able to rely rather a lot on my rudimentary programming abilities. I’m scoping out nationwide and native alternatives for information that is perhaps useful for my future initiatives. I hope to have one thing to share on the subsequent MQ DataMind occasion! 




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