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EARL 2021 will start with a week of afternoon workshops, hosted by our expert Mango Solutions Data Scientists.

This morning I (Laura Swales, Community and Events Manager) caught up with Alejandro Rico who is hosting the ‘Introduction to Shiny’ workshop to find out more about him and what people can learn from his workshop.

Hi Alejandro! Could you tell us some background information about yourself and what you do at Ascent?

I started with maths and statistics and trying to use that knowledge somewhere in business. More often than not, the decisions I made for businesses were automated – normally when you are a Data Scientist you just process a lot of information and interpret this in some way. But often those decisions are quite simple – for example, if X number is higher than X threshold, then green light. You then normally end up automating all of that, once you automate that information then you end up probably building a nice looking UI – so the product team can already check those numbers and say: ‘ok, we’ve got the green light from the maths shenanigans!’ – so I specialised doing that, not so much on the statistics part of things, but on the automation and nice-looking UI part. This eventually became Shiny development, so I joined Ascent (Mango Solutions) exclusively as a Shiny developer.

During my time at Mango, I’ve been developing Shiny – for different companies and different Shiny applications, but all Shiny! This is still a broad term because sometimes you spend a lot of time on the UI part – like designing the UX flow and how the user should interact with the tool, and on some other occasions, you spend time on the data processing part – which is closer to what a pure Data Scientist would do, but it’s part of the job still. I also deliver training on Shiny as well.

You’re hosting the Introduction to Shiny workshop at EARL online this year – what can attendees expect to learn?

I want to explain some basics with this workshops – getting people up and started on Shiny. I also want to sell Shiny! By that I mean, showcasing what you can do with Shiny and what the applications can be used for. I hope that once people are convinced of the advantages of Shiny, then the chapter on how to build your first Shiny app will be even more exciting. So there are two parts – selling Shiny and getting started with simple applications using Shiny.

Why do you think people should use Shiny over other tools?

The main reasons are when you look at what tools or framework you want for developing stuff you usually have to choose between something that’s easy to use or something that is powerful. I believe Shiny is an interesting framework as it’s extremely simple and easy to use for those who might not know about web app development. You only need a basic knowledge of R to use it and to get started pretty quickly. For anyone who wants to get started on web application development, Shiny works because you can start quickly but know that you can invest more and build more complex apps over time.

What is your favourite thing about Shiny?

Really what I said before – it’s flexibility! You can just use R and not ever realise behind the scenes it is using HTML and CSS, but if you really want to (and I do) you can be specific and flex your javascript knowledge. Shiny can have lots of small widgets where you can embed your javascript code – and I think that’s really cool. It has helped me to do unique things in the web app development world.

Thank you Alejandro!

To find out more about Alejandro’s Introduction to Shiny workshop – please view here. The workshop will take place on Monday 6th September from 2 pm-5 pm UK time and will be £90. Profits from EARL online will be donated to DataKind UK.

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The final day of the Enterprise Applications of the R Language Conference will be a day full of presentations from speakers who use R at work. It will be a great opportunity to hear from a variety of industries and how R is helping them in enterprise.

This closing day of EARL will take place on Friday 10th September and will run all day on UK time. The tickets will be priced at £9.99 – as the event is online we have far fewer overheads, and we will be able to donate our profits to DataKind UK.

We are pleased to also announce that EARL has been DICE (Diversity and Inclusion at Conferences and Events) certified and approved. The DICE organisation aims to encourage event organisers to think more about who they put on stage and to improve representation at events.

Agenda highlights

Of course, we are excited about all the talks at this year’s EARL, but we’ve selected just a few to highlight on this blog.

Dr Jacqueline Nolis, Saturn Cloud – Keynote
Jacqueline will be our first announced keynote speaker – she is a data science leader with over 15 years of experience in managing data science teams and projects at companies including DSW and Airbnb. She is currently the Head of Data Science at Saturn Cloud, where she helps design products for data scientists. We can’t wait to hear from Jacqueline’s vast experience of being in the data science field.

Avision Ho, Mettle – Meeting citizens where they R
Avision’s talk sounds like an excellent example of using open-source software to improve citizen access to meaningful information. He will cover specific technical elements of building a robust CRAN package and a mobile-centric Shiny app, as well as good DevOps practices that facilitate standardised and easy collaboration.

Daniel Durling, Bank of England – We are not start-ups!
Daniel’s talk touches on a host of oft-experienced cultural/operational barriers to doing data science in larger organisations, such as making the switch to open-source software and dealing with legacy code. We are looking forward to hearing how Daniel navigated this in the Bank of England.

Adithi Upadhya, ILK Labs – Shiny apps for air quality data analysis – Introduction to network analysis
Adithi is a co-founder and co-organiser of R-Ladies Bangalore and currently works as a Geospatial Analyst at ILK Labs Bangalore. Adithi’s talk will focus on creating Shiny applications to analyse and visualise air-pollution data. With pollution and air quality as hugely topical subjects, it will be fascinating to hear how Adithi and her team are managing the vast amount of data and creating meaningful Shiny apps.

To see the rest of the agenda, please visit our EARL page here. Alongside the presentation day, we are also hosting four workshops from Monday-Thursday (6-9th September 2021): Introduction to Shiny, Package Development in R, Functional Programming with Purrr and Web Scraping and Text Mining Lyrics in R.

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We are pleased to announce that we have selected DataKind  as the chosen charity that the Enterprise Applications of the R Language Conference (EARL) will support in 2021.

Last year when EARL needed to move online, we decided that as our overheads were lower we could donate our profits to charity. As we are online again, we are pleased to be able to do the same this year. We interviewed Suzy East, DataKind’s Community Project Manager, to find out more about the great work they do.

Tell us about DataKind’s mission?

Our mission is to transform the impact of social change organisations by building their capacity to use data science through:

  • Changing attitudes

We want to increase understanding of and trust in data science within the social sector, by showing what’s possible and how data can be used responsibly

  • Providing a safe space to test ideas

We work with organisations to explore what might help them, and introducing them to new approaches and tools

  • Supporting data practitioners

We provide access to peer support networks for data experts in the social sector, and we’re working to ensure the number of data scientists in social change organisations continues to grow

In order to achieve this, we run a number of programmes ranging from our monthly Office Hours, where any social change organisation can receive an hour of free advice on any data-related topic, to our DataDives, a high-energy weekend of exploratory analysis for one to three carefully selected charity partners, to our DataCorps, projects of up to one year where we can build and operationalise a data science tool to help an organisation work smarter.

Since we were founded in 2013, we have worked to understand the social sector’s needs and how we can harness the power of pro bono data scientists to deliver social impact. All of DataKind’s projects are undertaken by pro bono data scientists; we have a core community of around 50 active volunteers and work with several hundred over the course of every year. We are powered by this community of passionate data scientists – including statisticians, data engineers, visualisation experts, developers, designers and project managers – who have contributed over £3 million in pro bono data services through DataDives and DataCorps projects to more than 80 charities. We are now, by far, the most experienced provider of charity data science support in the UK.

Can you give us some examples of the kind of work you have done with social change orgs?

Example: Centrepoint

Centrepoint, a youth homelessness charity, came to their DataDive with a mound of messy local authority data. After much data cleaning, the volunteers created models to show that official government numbers underestimate the number of homeless people by a factor of 10. At that time, official government figures showed that there were 16,000 young homeless people in England. Our volunteers found that figure was more like 140,000. This project was the start of a two-year Centrepoint programme to develop a robust and accurate Youth Homelessness Databank for the entire sector, building on data contributed by charities and local authorities all across the UK.

Example: The Welcome Centre

We worked with the Welcome Centre, a food bank in Huddersfield, to identify those most likely to need extra support, over and above food packages. Four DataKind UK volunteer data scientists and a Welcome Centre trustee embedded a machine learning model in the food bank’s referral system. The model enables advisors to fast-track support to high-need cases. It identifies clients who were likely to become dependent early in their journey, enabling them to get extra support and advice to prevent temporary crises from becoming more permanent. This project was a finalist in the European Data Science Awards 2019 for Best use of Data to achieve Social Impact.

Has Covid affected the type of projects you have worked on?

Covid hasn’t necessarily affected the types of projects we work on, but it has massively impacted how we work. We used to run in-person DataDive weekends of up to 100 people, as well as in-person monthly office hours, volunteer committee meetings and training sessions, and much more! We’ve translated all our events and activities online, and while we miss seeing our wonderful volunteers and charity partners ‘IRL’, it has opened our events up to a new audience that couldn’t attend previously due to the distance, caring commitments or other factors. As a result, we definitely plan to keep holding regular online events in future.

As for our charity partners, it’s made it much more difficult for them to find the time and energy to engage in data projects with us, as many people have been furloughed, and many charities have had to prioritise delivering direct support to their beneficiaries. 

What are your main aims for 2021?

We are about to hold Data4Good festival on May 10-12, an online conference about data in the social sector. We are also currently working on developing an updated strategy for the next three years, with the help of our board of trustees. In terms of projects, we’re looking to deliver three DataCorps projects, along with our regular DataDives. 

If someone is reading this and wants to find out more and ways they can help, where can they go?

If you’re a data scientist or data analyst that wants to get involved, we recommend you start by taking part in one of our DataDive weekends. Take a look at our website where you can read more about volunteering with us, and sign up to our mailing list to hear about future events.

Thank you Suzy! We look forward to working on some events and partnerships with Data Kind UK in the lead up to EARL 2021.

Tickets are now on sale!

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First held back in 1974, World Environment Day has become a powerful way for the United Nations to engage with “governments, businesses and citizens in an effort to address pressing environmental issues.” This year, a key theme is #GenerationRestoration and also sees the launch of the UN Decade on Ecosystem Restoration: a global rallying cry for everyone to do their part in healing the planet.

Back in the 70s, the prospect of a looming global environmental crisis was, for most people, simply not among the major issues of the day. Experts and activists aside, few could have imagined the pace at which events would develop and how urgent the need for action would become.

In a similar way, half a century ago, the idea that technology could have a positive impact on protecting the planet was much closer to science fiction than reality. Today, however, the world looks to digital innovation as one of the main strategies to combat climate change, with data science among the industries now playing a vital role on both a macro and micro scale.

Globally, data scientists blend human expertise with technology to assess data and review the impact of problems causing climate change. This insight informs government policy, which then filters across the economy and society to deliver meaningful impact. In the UK, for example, it is now national policy to cut carbon emissions by 78% by 2035, and data science will play a key ongoing role in the further development of policies in the years ahead.

On a day-to-day basis, businesses everywhere will need to make a major contribution if this target is to be reached. The sustainability of every organisation depends on addressing the impact of its operations across the supply chain. Everything from water consumption, pollution and plastic reduction, to carbon emissions, waste and recycling, is part of the equation – and data science modelling is increasingly being used by businesses to assess the likely impact of their actions and the quality of decision-making.

In recent years, the Mango team has worked on sustainability projects to monitor and measure world poverty, reduce water waste and to understand the proportion of electricity generated using low-carbon sources. We remain committed to broadening the availability of data science expertise and technology to make a difference to ensure data science empowers #GenerationRestoration.

Delivery by Mango

Protecting and preserving biodiversity

Mango built and mentored several data science production projects across the ONS including the United Nations funded Sustainability Development Goals, a system to monitor and measure world poverty based on 19 sustainable goals, from ending hunger and poverty to achieving sustainable energy and gender equality to protecting and preserving biodiversity. Data science is a powerful tool which can be used to inform businesses and improve their water consumption as well as having world-wide applications in reaching the UN targets of providing clean, accessible water to all.

Reducing water waste

Mango helped i20 realise their data capabilities but develop a solution that greatly improved the performance of their smart network solutions, leading them into the world of AI and data analytics. This has enabled water companies to shift to conditional based maintenance and reduce the number of water leaks. One client reduced leakage by 15% in the north of their city within 2 weeks of using the solution.

Enabling the adoption of renewable energy

Britain’s first all-digital, renewable energy supplier Pure Planet choose to work with Mango to harness their data to drive data-driven pricing solutions and help to drive service efficiency. Mango added value in terms of broadening the scope and skills of the data science team and in helping them to establish common frameworks and processes to make data science easier with repeatable and scalable models.

Assessing the proportion of low carbon sources of energy

Mango were involved in a project that assessed the proportion of electricity generated using low-carbon sources including solar, wind, hydro or nuclear. All the data and deployment workflows were developed to schedule daily updates of carbon intensity data and re-deploying the app when the data was pushed to main branch.

Data science is used widely in business as an integral part of a businesses to positively impact change in a number of ways https://earth.org/data_visualization/ai-can-it-help-achieve-environmental-sustainable/

Data scientists, looking to add their support to the wider effort to protect the environment, can get more information from the Open Sustainable Technology website which provides a list of all sustainable, open, and actively maintained technology projects worldwide and details of how to get involved.