Big Data 2020

BigDat 2020

6th International Winter School on BigDat
Department of Information Engineering
Marche Polytechnic University

Ancona, Italy - January 13-17, 2020

Big Data in a growing field with ties into a number of academic tracks. The variety of sources, applications of Big Data create a large spectrum of challenges and advances which have potential for huge impact on scientific discoveries in business models, society, medicine and numerous other fields. BigDat2020 brought together researchers, academics and industry pioneers to facilitate learning, collaborations and idea sharing. 

During the winter school seminars and lectures were put on in a number of areas such as, major challenges of analytics, infrastructure, management, search and mining, security, privacy and applications. Alongside these courses from a number of inspiring speakers, the event also hosted daily lunches and breaks which motivated active and promising interactions from research students. Below are some reflections of my experience at BigDat2020.

18th Century Insights into 21st Century Problems

During the winter school Rory Smith (Monash University) ran a series of lectures on 'Learning from Data, the Bayesian Way'. The goal of these lectures was to take a Bayesian look at statistically optimal ways to detect and extract information in noisy data. This lecture series addressed a range of Bayesian related topics from inference and parameter estimation to sampling methods and hierarchical inference. Coming from a pure mathematics degree these lectures appealed to me the moment I saw them in the schedule. An early slide in the course read "18th Century Insights into 21st Century Problems". This really resonated with me. My PhD is an interesting hybrid between the application of mathematics into modern issues such as poverty and development. Often in my literature review I have come across papers from over 100 years ago and yet the mathematics not only still hold but is fundamentally routed and often unchanged in work done today. There is something beautiful about this. It's like visiting an old cathedral and admiring the strength of large pillars which have stayed standing through years of weathering and generations of visitors. 

Bayesian methodology is a statistical tool introduced by Rev.Thomas Bayes in the 18th century, yet it is vital in providing solutions to a variety of statistical issues and problems presented by researchers today. It's incredible! Bayes approach can be used to compliment a range of statistical methods and I would recommend researchers from any field look into learning some basic Bayesian statistics to see where they could be used in their work.  

Accessibility

Another thing which stood out to me at this event was accessibility. Big data is such a broad topic and is applied in so many fields now that scoping an event tailored to all these fields is inevitably difficult. People attending this conference ranged from pure data scientists and statisticians with intricate knowledge of a range of big data areas, to people from humanity schools looking to learn what big data is to apply it to their work. Knowing this I was pleased to see that the schedule of the events include a vast range of understanding requirements for different talks. Everyone was able to pick talks which suited their needs. Many of the talks though-out the week were however given as a follow on to previous talks in the week on the same topic. The meant that there were some big leaps within and in between talks. You could sit in an hour long talk and spend the first 20 mins feeling like you were not learning anything, then be totally lost by the last 20 mins. I think this is an inevitable part of interdisciplinary work, there will be moment when you feel things are too basic and moments of overwhelming confusion. This can really feed into imposter syndrome. What I did like about this event is that there were ample resources online provided after each talk which pointed people in the right direction both for learning the basics and extending topics to more complex levels. PhD can be very isolated, you work on a tiny specific area of what you do, and often you are the only one doing it. Sometimes you might read a paper or article which leaves you totally baffled and not even knowing where to look up the information you would need to understand what the paper was talking about. Events like this help to combat these issues of accessibility and imposter syndrome - they unite people and present an opportunity for experiences to be shared and questions to be asked.

My presentation


During Big Dat I presented a summary of my recent work. One thing I talked about during my presentation was data cleaning. After this presentation someone approached me and explained that they had experienced similar 'messy data' issues in a completely different dataset and field of study. This sparked a really interesting conversation about the challenges we have both faced and led to us both going away with various notes on our phone of 'Things to look into'. Without the opportunity to present this conversation would never have happened. If I could speak to my younger self of future researchers starting on the PhD journey I would encourage them to take every possible opportunity to present their work. Not only will the practice build their confidence presenting and spark useful feedback and discussions but they will also get to know their work better and be pushed to clarify aspects of work. 

It's a boy thing...

Another reflect I had of this week is an ongoing reflection throughout my educational experience. I did my undergraduate degree in mathematics. Many of my lectures, seminars and tutorials showed disproportionally many boys compared to girls. This was also reflected in the teaching staff on the course. At the time I remember questioning it and thinking why is it like this? At what age does this separation start? Who's responsibility is it to engage young women in the field? Sitting in my first talk at Big Data I was brought right back to all those questions. I picked the more technical of the two morning sessions and in a room of nearly 100 people I could only spot about 5-6 girls. Although not as extreme, the rest of the event also had notably more boys in attendance than girls. The gender gap in the professional world is closing, albeit slowly. However the data science and more broadly tech industry are still lagging behind despite being considered a modern field of work. Problem in the work force such as pay gaps, marginalisation and discrimination are not born in the work place, they grow throughout our education. I am lucky enough to be a part of a number of different projects involving young people. After coming back from this event I am inspired to talk to these children (both boys and girls) about the wonderful world and opportunities in STEM. 

There are big questions around this. What causes these problems? And more importantly, what can people along the education path, and working in the data science industry do to solve it and be more inclusive. It could take a lifetime to answer these questions, but I want to take these thoughts with me in my career. Whatever I end up doing I want to use my research (PhD and beyond) to show young people just one of the many incredible uses of STEM knowledge.

Gratitude


This is the final year of my PhD... the famously dreaded write up year. I am certain there will be points when I wonder "Why did I do this?" "Can I do this?" "Will it all be okay?" I know I will get wrapped up in various bubbles of stress and panic. 

Fact.... It's gonna be tough! 

That being said, I am currently writing about the reflection of an academic event I attended in Italy. An event where I learnt all sorts of things about statistics, data visualisations and problems of privacy in big data among other things. An event which led me to meet all sorts of fascinating people at various points in their career researching a range of things from road safety to spread of disease. An event which allowed me to see Ancona, a city founded by Greek settlers and today one of the main ports on the Adriatic Sea with a colleague and close friend. An event where I had the opportunity to present my work and get feedback from knowledgeable experts allowing me to improve my work. How wonderful right?! 

This is just one of the many things which had happened to me because I became a PhD candidate. My approach to getting through this year is to pop my stressful bubbles with gratitude. Before writing this Big Data reflection I wrote a list of things which I am grateful for through my PhD. Random items from this list are now scheduled to pop up at various points from now until my completion date, giving me some much needed perspective. No matter how stressful I find this year, it's a privileged stress to have and I intend to appreciate as much of it as possible. Here are just a few examples of things I am grateful for. 

Coding - Early on in my PhD my supervisor encouraged me to take the time to make friends with Python. I couldn't have even considered the opportunities and doors this skill will open before I started. 

Mathematics for Development Bridge - However nerdy and cheesy its sounds I love maths and I love helping people. This PhD has shown me that there is a place for both. I can be a part of work with real impact without giving up my love of mathematics.


People - Where to start with this one? The range of wonderful people I have met through this PhD is incredible! I've met inspiring people who are doing incredible work, like-minded people, people from totally different lives and fields to me and, people who have become lifelong friends.

These are just three of a long list, but there is so much more; seeing the world, personal growth and awareness among other things. For any fellow PhD students in their final year... we got this! 

Key Take Aways


Maths is timeless and beautiful! (And have a look at Bayesian Statistics) 

Scoping large interdisciplinary events is hard, but worth it! 

There is more to be done in terms of gender equality, and I want to prioritise this in my own career. 

I wanted to do this PhD - and my gosh am I grateful for the opportunities it has given me!
Share by: