Data Learning and the social good
What role can open data have in the community? Hear from Ian Watt on his reasons for studying data science.
1. What's your name, where are you from, what are you studying?
My name is Ian Watt, and I'm from Aberdeen. I'm studying for MSc Data Science at Robert Gordon University in Aberdeen.
2. Why did you decide to get involved in data science?
I recently retired from Local Government where I led teams which managed some of the council’s main data assets. I introduced the concept of Master Data Management and Open Data to the authority. I recognised the value of data both as a tool for business intelligence and as a driver of efficiency and effectiveness in service delivery, but there was no data science capability in the council and the practical side of that interested me. Having studied informally through MOOCs such as Coursera, when the opportunity came up to study for the MSc I jumped at the chance.
3. What kinds of topics did you cover as part of your course?
So far, we have studied:
- Data Warehousing – how data is managed for better business intelligence, with a focus on Microsoft tools such as SQL Server, the use of data marts and data warehouses, how to set up and query data cubes etc.
- Advanced Data Management – using modern technologies such as Hadoop to manipulate and analyse ‘big data’ in a way that would not be possible using conventional tools and programmes.
- Data Mining – using advanced techniques to extract value and intelligence from data. This is the foundation of Machine Learning: designing or using algorithms to learn from data and make predictions.
- Information Retrieval – working with unstructured data and large bodies of documents, indexing, searching and retrieving information, and extracting value and intelligence when coupled with data mining techniques.
4. What work opportunities do you see with your training – what would you like to/what are you doing now?
The topics, skills and techniques which we are studying are applicable to any domain or subject area. I co-founded an organisation called Code The City a few years ago which aims to use technology and data for better civic outcomes. I am driven by that idea of social purpose – how can the skills which we are developing be used for social good? How can we work with the public and private sectors to make their data available as Open Data – and how can we help the public understand and make use of that data?
5.How do you think data science is relevant to small to medium sized businesses and communities?
Existing SMEs can use data science skills to better understand their customers, their processes and develop new markets. SMEs could also be set up by graduates who want to work for themselves to support other businesses.
There is a growing movement of Open Data in Scotland. The Scottish Cities Alliance have been working with the 7 Cities, for example, on developing a network of open data portals – and activities to get people involved in using that data to better understand the decision-making process, but also to build innovative new products and services based on that data. This will have significant social and economic benefits for the city regions. Outreach programmes should create opportunities for citizens to get involved and for Data Lab students to pass on some of their skills.
6. What real life examples of innovative data usage have you seen/studied that you think demonstrates its benefits to society and/or business?
In the open data field, the case of Transport For London stands out. Rather than develop apps, which was not its core business, it was persuaded to make all of its data available as Open Data, including timetable and real time information on buses, trains, tube and even community bikes. This saw a number of start-ups formed who developed high quality apps for navigating the city. A recent study showed that for every £1 spent by TfL on publishing data openly, London as a whole benefited by £30. That is an amazing ROI and also shows the importance of looking at the benefits to the broader population.
In Rio De Janeiro, a new app CrimeRadar uses data from a large number of sources, coupled with data mining and machine learning, to help predict crime and to assist citizens to understand the difference between perceived and actual risk of crimes in areas of the city.