Category: Collaboration and Data

The importance of Data Storytelling

Posted on by in Collaboration and Data

In the age of big data, it’s not enough to simply collect and analyse data – you need to be able to effectively communicate your findings as well.

That’s where data storytelling comes in.

Data storytelling is a concept that you define in a simple way of complex data analytics aiming and informing a target audience. This practice has gained popularity in recent years as a means of engaging and informing audiences through interactive graphics and narratives.

Data Storytelling in Local Government Authority has been particularly effective in presenting complex data to its residents, helping residents understand important information and improving transparency between government functions and the public. To effectively communicate data insights, data storytelling techniques help to create a compelling and easy-to-understand narrative supported by engaging data visualisations.

Data Storytelling is a natural form of passing information, as it engages with the audience and stimulates their attention through emotions. This approach is particularly effective in conveying information that would otherwise be difficult to understand through raw statistics or technical reports. It is a crucial skill for any data professional or organisation that wants to effectively communicate insights and facilitate better decision-making based on their findings.

How to process information in 6 steps?

Ensuring setting clear objectives is the first step in the data storytelling process. Next, what and how data must be collected and analysed using appropriate tools. Once the data is analysed, it’s time to identify key insights and develop a clear and compelling narrative that supports those points.

image highlighting 6 steps of data storytelling process
Source: LBH Self-Designed

6 common mistakes to avoid?

There are several common mistakes to avoid when implementing data storytelling practices, including:

  1. Picking up a wrong chart, for i.e., 3D charts look great but not easy to read or interpret.
  2. Incorrect use of colour correlation, for i.e., using low contrast colours or colours that are too similar, can make it difficult for viewers to distinguish between data points, categories, or trends.
  3. Missing out supporting guidance, labels, or tips alongside visual segments
  4. Too many data visuals in a small dashboard space.
  5. Ignoring accessibility standards when selecting colours or font sizes in data storytelling can have a detrimental impact on the inclusivity and usability of the visualisations. For i.e., Ignoring colour contrast guidelines can make it difficult for individuals with low vision or colour blindness to interpret the information.
  6. Not aware on audience needs and their expectations.
image highlighting 6 common mistake in data storytelling.
Source: LBH Self-Designed

Few Good and Bad Examples

image highlighting 4 example of data storytelling good and bad practices
Source: LBH Self-Designed

Further takeaway points for you

Exploring Hounslow in forms of a Scavenger Hunt

Posted on by in Collaboration and Data

There are many ways to do team bonding exercises for your team for example building spaghetti houses, or debates. However one of my colleagues thought outside the box and decided to exercise us all to venture out into the borough and take part in a scavenger hunt.

Myself including my team were kept in the dark about the event until the day and had no idea how the day would pan out. We had a meeting point on the 6th floor to have the rules explained to us and then also split into two teams: team savage (I was in that team) and team ramblers.

We all got handed these mysterious brown envelopes which felt like it includes some sort of top-secret mission inside. Funnily enough, pulled out the piece of paper inside and the scavenger hunt guide was titled ‘WELCOME TO THE FIRST, BEST AND POSSIBLY THE ONLY GREAT HOUNSLOW BOROUGH COUNCIL TEAM DATA SCAVENGER HUNT’

This followed by some instructions which said we had two hours and that some of the clues are relatively straight forward and that we need to take photos with our phones of what we think is in relation to that clue. Bear in mind that we have to put ourselves into our colleagues’ shoes or more like her brain. We all seemed clueless looking at these clues!

Here are the ‘targets’ below:

TARGETS

1. A photo of your team – as original as possible, please!

2. A photo of the other team taking a photo of a target.

3. 100021547143

4. Gules three Seaxes fessewise in pale proper pommelled and hilted Or points to the sinister and cutting edge upwards in chief a Saxon Crown of the last

5. Streetlife

6. They would not listen, they’re not listening still, perhaps they never will.

7. Wildlife

8. HS6

9. A sarsen stone

10. A replacement for a victim of arson

11. Best.froth.anyway

12. Beauty in ugliness

13. A barber / hairdresser

14. Shiny Shiny Sheppard Robson

15. A memorial

16. A pre-2000 phone number

17. 3132071

18. Is it all going for a Burton? Do you need a little Xtra help?

19. It tolls for thee.

20. Write a Hounslow-inspired limerick.

So fair enough there are some simple clues such as barber/hairdresser, but I had no idea what most of these clues meant. Thank goodness I wasn’t on my own and was in a team where we could figure out what these all meant – also, we were allowed to use Google! Hooray! (-:

All the while, our colleague who created the scavenger hunt was walking around Hounslow trying to find us and take photos of us looking absolutely confused… Team Savage below:

At first, we didn’t know the area range of these clues, but most seemed to span out across the Hounslow High Street. We found out that one of the clues ended up at the Air Quality HS6 in Heston which is a half hour walk away – team Ramblers found their way there!

There were some clues in relation to our project work as well (air quality being one of them), such as 3132071 which is Grove Road Primary School. If there was no context to this photo, it would look weird to take it in front of the school’s sign BUT here is a lovely photo of others in the Data Quality and Science team, Team Ramblers:

This day proved to be such a great learning experience. I have lived in the borough for about 13 years now and have learnt more in a day about the history of our borough than the last 13 years! It really opened my eyes and made me appreciate our culture.

I’m hoping this provides some inspiration for other teams to explore Hounslow in another set of eyes and really get to know the borough.

My highlight of the hunt was spending time with my colleagues, visiting the Sarson stone and the painted house of Vincent Van Gogh.

Photos of the answers

Below is the photos of the answers to the scavenger hunt! Have a crack at it and try and pair these photos yourself with the targets.

Thanks all for reading. If you do plan your own scavenger hunt, let me know how it went and even post your own blog post for us to all read about!

Exploring Hounslow’s Air Quality Data

Posted on by in Collaboration and Data

Why Air Quality matters?

It is a known fact that poor air quality is unhealthy to all of us, especially for vulnerable groups such as people with medical conditions such as heart issues or asthma, as well as children or the elderly with breathing difficulties. Air quality is not the same everywhere. In other words: pollution can build up in pockets and we call them “hot spots” and potential reasons for these occurring are that they are close to a busy road or near a commercial or industrial zone. Prevailing weather conditions are another contributory factor that impacts air quality measures. So, it is important to us all to monitor air quality regularly, identify troublesome “hot spots”, and ensure that we are using this information to help guide actions and policies focused on ensuring cleaner air for us all.

What do we know about Air Quality in Hounslow?

London Borough of Hounslow partners with Ricardo Energy & Environment who maintain 6 Air Quality monitoring sites across the borough. As well as these sites, there are also third-party monitoring stations like Breathe London. Live stations provide hourly data which hold key measurements of specific pollutants within the air. The current list of live monitoring stations is as below:

  • Brentford
  • Chiswick
  • Feltham
  • Gunnersbury
  • Hatton Cross
  • Heston

Quick understanding of Air Quality measures (Pollutants)

Do you know that air is mostly gas? Air is actually comprised of a mixture of different gases like Nitrogen (approx. 78%), Oxygen (21%) and the remaining approx. 1% hold lots of other gases in the earth’s atmosphere (NASA). The UK Government has provided a national legislation and standards on air quality that identifies key pollutants in the air, like Nitrogen Dioxide (NO2), Particulate Matter up to 10 micrometres in size (PM10), Small Particulate Matter under 2.5 micrometre in size (PM2.5), Nitric Oxide (NO), Sulphur Dioxide (SO2) and Ozone (O3).

How can data science support a ‘data-enabled decision making’ process?

The role of data science brings in a deep lens to interpret data with a new dimensions and opportunities. With the use of key data science technologies like Python and R, you can filter out answers in seconds. At the London Borough of Hounslow, the Data Science & Quality Team have been working on air quality data sets generated during the last 10 years, where we have learned and identified valuable insights such as, seasonal changes impacting the hot spots’ live feeds, last 10 years comparison between hot spots and its performance to gather data, correlating pollutants with each other, correlating data with 3rd party monitoring stations, engineering and deploying machine learning models for predictive insights and utilising cloud technologies for rapid outcomes for data-enabled decision making.

During our data science work, we have learned so many facts and picked up patterns based on air quality data insights, do you know that during winter season pollutants concentration within the air stays longer than summer because cold air is denser and moves slower than warm air. The image below explains last 10 years of seasonal recordings within Hounslow.

data visual for Air Quality and its pattern during seasonal changes.
Air Quality Pollutants / Visual covering yearly seasons

What can we do in future?

The Data Science & Quality Team regularly meets Environmental & Public Health colleagues and are working on future initiatives for the cleaner air in Hounslow. One of the future initiatives is to correlate past 10 years of air quality data against the public health’s respiratory datasets. This initiative will bring in new dimensions and thoughts to build on.

If you have an idea / suggestion to share or to correlate Hounslow’s Air Quality data against your datasets, then please do approach us.

Understanding Machine Learning (ML) in 5 Minutes

Posted on by in Collaboration and Data

By Ejaz Hussain – Lead Data Scientist

What is machine learning?

To make it simple and short, “machine learning is one of the foundational branches of Artificial Intelligence (AI) which focuses on the use of data and mathematical based calculations (algorithms) to imitate the way we (as humans) learn, and then gradually improve its accuracy to predict outcomes (results)”.

What is predictive modelling in machine learning?

In a nutshell, predictive modelling is “a statistical technique using machine learning and data processing to predict and forecast likely future outcomes (results) with the support of historical and existing data”. Predictive modelling works by analysing historical and current data where it projects what it learns using a model ‘forecasting likely’ outcomes.

Machine learning examples and initiatives

Machine learning practices has helped many businesses in both private and public sector and potential for opportunities are unlimited which really support local businesses to achieve their targets. To make it more relevant for the London Borough of Hounslow, here are few examples which have acted as a driver for a greater change.

  • Data Science helped identify potential savings of over £581m for the NHS – click here to view detailed article.
  • Leeds Institute for Data Analytics using machine learning in a completely new way to improve climate models – click here to view detailed article.
  • Data Science to tackle ‘global targets for sustainable development’ which are set by the United Nations – click here to view detailed article.

How Data Science and Predictive Analytics can contribute to sustainable development

In the past, data science practices were limited to the top fortune 500 global businesses, however; there is a larger shift where data science is now adopted by nearly all private and public sector organisations which is mainly due to big data ease of access and reduced costs of using open-source technologies.

The illustration below is one of the examples, set by the United Nations where the focus is on data science and analytics. In this example, data is an integral part where we (London Borough of Hounslow) can step in and support the common goal which is to make our world safer and sustainable.

Source: United Nations – Data Science Contributions towards SDG’s

Understanding Data Science and Data Quality

Posted on by in Collaboration and Data

As part of the digital strategy, the London Borough of Hounslow (LBH) now have a Data Science and Data Quality Team.

We interviewed the team to get a sense of what the Data Science and Data Quality Team will be working on.

The team

Ejaz Hussain, Lead Data Scientist

Anna Trichkine, Data Quality Lead

Ahmed Babalola Lasisi, Data Engineer

Neil Gordon, Data and Development Manager

What does Data Quality and Data Science mean to the team?

Data Quality:

Data Quality is a focus area for many teams. Data Quality can be developed in many ways including focusing on data engineering and creating good data pipelines, running regular data quality reports, and visualising data to showcase the quality to users.

Anna

Data Science:

The role of data science is unique and stands between the business operational world and the technical world. Data Science offers opportunities of deep data analysis where artificial intelligence technologies such as machine learning play a vital role to design and build predictive models. Such predictive models run on algorithm-based principles and help us to achieve business specific outcomes, for example data enabled decision making.

Ejaz

Data Science and Data Quality:

This is a genuinely exciting time at Hounslow, with the creation of a dedicated Data Science and Data Quality Team helping to leverage data as one of our most powerful assets driving greater sharing, analysis and insight across all areas of the council. Predictive modelling, AI and machine learning are all dependent on data quality so combining both disciplines within the new team provides a wonderful opportunity to progress at pace and deliver real value to colleagues and constituents alike.

Neil

What are the 3 things you love most about your role?

Ejaz:

 1. I love to explore complex data and to predict the best data-enabled options moving forward so that the London Borough of Hounslow and its residents can see real benefits

 2. I love to be able to see hidden opportunities and then interpret such opportunities for wider good

 3. To learn and share data science activities (like machine learning) with collaborative channels such as LOTI (London Office for Technology and Innovation)

Ahmed:

1. I love data engineering because it involves picking pieces of data from diverse sources and integrating them for data driven decisions

2. Consolidating and cleaning the data to create data pipelines

3. Working within the data quality and data science team to make sense of the council data that will support the council’s data-enabled decision making

Anna:

1. Data Quality is like solving puzzles and having the opportunity to solve puzzles is so fun

2. Data Quality tasks are not restricted to any single tool and provide opportunities to constantly upskill in either new programming languages, or new tools, or both

3. Data Quality is something that is important for every team and having the opportunity to work with every team means that you feel integrated into the council very quickly

Neil:

1. Transforming unstructured, poor quality data into intelligence, insight and learning that informs decision making and delivers positive customer experiences

2. As a fellow ‘data geek’ who cut his teeth processing name and address data on mainframes, I really enjoy seeing how technology has evolved and enables the Team to cleanse, analyse and visualise data seamlessly

3. Collaboration and team building

What are your favourite things about working for Hounslow Council?

Ejaz:

1. I love the positivity and engagement throughout the Council

2. Trust and excellent support from line management

3. Able to speak up and contribute positives ideas and thoughts with others

Ahmed:

1. The London Borough of Hounslow is a hub for collaboration and openness

2. Good working environment, although working remotely

3. Opportunity for training and growth

Anna:

1. I live in the borough so I love learning about all the work that is being done to support local residents

2. Hounslow House is a beautiful building to work in

3. The focus on inclusivity in tech is an area that the council are working hard to support and it is closely linked to my own values

Neil:

1. The challenge of building new teams, technology, environments and processes

2. Independence, opportunity to influence strategy, direction and collaborate with internal and external colleagues

3. People!

Hounslow and Open Data

Posted on by in Collaboration and Data

The London Borough of Hounslow is committed to playing a full part in the local government open data agenda. Here we outline the essential elements of our approach.

What is open data?

Open data is non-personal data that is made freely available to be used, reused and redistributed by anyone.

To qualify as open data a set of data should have the following characteristics:

  • It should be published in an open format.
  • It should be machine readable.
  • It should be published under an open licence that allows for free reuse.

You can read more about the definition of open data in the Open Data Handbook.

Why should local authorities publish open data?

The Local Government Association (LGA) has argued that local government should encourage a meaningful approach to open data in order to:

  • foster accountability;
  • innovate and transform services leading to improvements and efficiencies;
  • empower citizen and community groups to choose or run services and shape neighbourhoods;
  • and drive local economic growth.

Greater transparency is at the heart of enabling the public to hold politicians and public bodies to account. Where public money is involved there is a fundamental public interest in being able to see how it is being spent, to demonstrate how value for money has been achieved or to highlight inefficiency.

Making public sector data available for use can also provide an opportunity for innovation by the public, business and third sector. New ways of using or interpreting the data, perhaps combining it with other sources of data, can be developed independently. With these new tools and greater understanding, a more informed public can make better decisions, both for themselves and the wider community, and develop new ways to solve problems.

Finally, publishing open data plays an important role for local government in meeting its legislative and regulatory obligations. For example, the local government transparency code requires local authorities to publish specific information about assets, expenditure, and staff salaries.

“We use Open Data to publish our information in relation to senior pay and our pay multiple, as required under the Localism Act.  It is useful to have a central place where this data is stored and available to colleagues and the public.  We link to this data in internal reports, and it is helpful to signpost enquiries to this site.”

Strategic People Services, HR & OD

The Hounslow approach to Open Data 

The council has committed to the timely and accessible publication of data about the full range of services we provide, the money we spend and the resources we hold. We will also seek to collect, aggregate and publish data about the borough of Hounslow itself and its economy and community.

We have decided that we will follow six open data principles:

  • We will publish open data by default
  • We will publish accurate and complete data
  • We will publish data quickly
  • We will publish data that is easy to access and use
  • We will continually seek to enhance the data we publish
  • The publication of our data will be responsive to the needs of our residents and will help support the delivery of services

In order to realise this commitment we have developed, and will continue to evolve and improve, a set of procedures and standards for the management of open data within the organisation. We have identified a number of roles with specific responsibilities for open data amongst staff across all levels and departments of the organisation. We have also invested in developing a dedicated online platform on which to publish and make available to the public our data.

Beyond the publishing of open data, the council will also seek to find new and innovative ways to use that data. We will seek to build tools, applications and services that make use of the data. We will look for ways that the open data can be used to improve service delivery and outcomes. We believe our new specialist data team will help us build on the progress we have made so far and that we will be able to increase the range and frequency of the open data we publish.

Our data online

The London Borough of Hounslow’s dedicated online platform for open data can be found here:

data.hounslow.gov.uk

Further resources

How to get the most out of your anonymous surveys

Posted on by in Collaboration and Data

By Anna Trichkine, Data Quality Lead

During a period of change, surveys are a go to tool. If my own experience is anything to go by, I would say you’ve probably filled out dozens of surveys over the last year and for most of these surveys you are yet to see the results.

The good news is that the survey results often have important stories contained within them, even if they’re anonymous.

So how can we retell the stories whilst still maintaining anonymity?

The data team at London Borough of Hounslow have recently been tasked with analysing the data for anonymous workplace surveys. These surveys aim to capture how participants feel about working in the borough, and how they feel about working from home. As the data that are collected are anonymous, it is important to try to find patterns or stories in the responses without revealing any personally identifiable experiences. The user profile must not reveal an individual but must provide an insight into a group of people with similar experiences.

How do we do this?

One way to do this is by using decision trees, a type of mathematical model that identifies patterns in your data set by asking true/false style questions.

Using this mathematical model we are able to identify patterns in the data set. The mathematical model takes into consideration all of the questions asked by the survey, and suggests which of these questions are more important. Even if a survey had dozens of questions, it may be that only two or three of the questions have significant differences for the way people respond.

Once these key questions are identified, the data team specify minimum sample sizes for each group to make sure anonymity is maintained.

This combined approach can build a compelling story whilst also making sure that the narrative is anonymous.

Results

Once the model identified the key questions, and the groupings, the team were able to build up a user profile from the grouped responses.

We were able to create 4 main personas, each with unique reflections and experiences of working in the Borough of Hounslow. Underneath these personas were the collective responses for a group of individuals who shared similar thoughts.

Relaying these stories as personas, rather than as graphs and line charts, allows the stories to come to life. We can empathise a lot more with a person, rather than with a line. In this way, the anonymous surveys become more exciting both for our team, and hopefully for those who would like to see the results of the survey.

We will be sharing the personas internally with staff, and would love to hear which persona resonates with you.

First step towards data science collaboration

Posted on by in Collaboration and Data

By Ejaz Hussain – Data Scientist and Anna Trichkine – Data Quality Lead

An exciting learning Journey with LOTI and ONS.

The Data Science and Data Quality Team at London Borough of Hounslow is a newly formed team within Digital and IT. The team is made up of Lead Data Scientist Ejaz Hussain, and Data Quality Lead Anna Trichkine.

As a new team, we will be working to improve data practices and data ethics within London Borough of Hounslow. We will be exploring new opportunities for how to use our data and how to make sure we are making more data-enabled decisions across the borough.

To begin with, we have been selected to join the pilot data science and machine learning programme run collaboratively by ONS and LOTI.

Who are ONS?

The Office for National Statistics, the government department specialising in everything data and statistics!

Who are LOTI?

The London Office for Technology and Innovation, working to support collaboration between 33 London local authorities.

What is the programme?

The programme focuses on developing the team’s expertise in data science, specifically to improve the quality of local government data by using programming languages; R and Python.

This is an 8-12-week programme and we will be meeting with the ONS mentors on a weekly basis.

During these weekly sessions, we review data projects together with the mentors along with other local authority participants who have also been selected to join the programme.

A picture of our first session together is shared below.

Zoom call screenshot of first data science programme session

How will this benefit London Borough of Hounslow?

We will be taking the learning from these sessions and sharing the tools and techniques with other analysts across the council.

We have been given access to the ONS learning pool, a hub of well-prepared learning materials, that we can share with staff across the council.

If you are interested in accessing this content or to find out more about our sessions, please email us and we will be happy to guide and support.

Thank you to ONS and LOTI for this exciting opportunity.  

Fibre broadband in Hounslow

Posted on by in Collaboration and Data, Place and Community

Current sites completed by Community Fibre as at June 2022

Community Fibre are now mostly complete and are due finish Council owned flats by end of July 2022 and have also commenced a wider rollout in the Borough to non Hounslow owned properties

Sites underway by Hyperoptic

Derwent Lodge

Brent Lea

Belvedere House

Spooner House

What is fibre broadband to premises?

This is the where the fibre cable is delivered direct into premises and not via the green boxes you may see which then need a copper cable into each individual property.

A fibre optic cable is able to handle a much larger volume of data than a copper cable without degrading. Fibre optic is therefore quicker than standard broadband, as the signal strength is less likely to fail with distance from the exchange, and speeds are maintained over greater distance. Maintenance is also better with fibre broadband and better guarantees of speed can be offered by suppliers.

The work also helps as part of move to fibre from copper by BT Openreach over the coming years with the current final date for disconnection set at 31 December 2025 for equipment connected from exchanges via copper to local “green” boxes.

Fibre broadband in Hounslow

The principles for guiding the roll out of fibre broadband:

  • To maximise the extent and coverage of fibre broadband availability for residents and businesses in the borough.
  • To deliver the rollout of improved fibre infrastructure in a way that minimises the disturbance to residents and businesses in the borough.
  • To ensure delivery of fibre broadband networks at pace.
  • To leverage social, environmental and economic value and secure investment in digital investment that everyone in the borough can benefit from.

The Council has been working in partnership with Harrow and Barnet Councils, so far Community Fibre and Hyperoptic have signed agreements with more expected, with the rollout programmes being developed currently for the Council’s social housing stock. This will help to unlock the investment needed to get fibre broadband into all premises in Hounslow,

Our first ever Digital Festival Hounslow

Posted on by in Collaboration and Data, Staff and Workforce

Wow, what an incredible month November was.  What started as an idea at the beginning of September turned into a 4-week reality and now it is hard to believe that our first ever Digital Festival Hounslow is over already.  The Festival was a resounding success and the figures speak for themselves:

  • Digital Festival Hounslow ran over 20 days 
  • We held 62 events of which 16 were open to the community
  • 7 events in partnership with local businesses including Chimni, See.Sense and our Community & Voluntary partners
  • Ran 3 events with two of our key digital partners, LOTI and SOCITM
  • 16 events in partnership with global business including Microsoft, Amazon and Google 
  • 6 events in partnership with Organisational Development 
  • 3 events in partnership with Public Health 
  • 26 events delivered by D&IT 
  • 2 Councillor led sessions
  • We had 80 different speakers​
  • ​We delivered over 55 hours of live content
  • 18.5 hours which was recorded and is available to watch back on our SharePoint site​
  • 10:30 has been uploaded to our YouTube channel for the public to view
  • Finally: ……. we had 2700 sign up requests!

We delivered events on Wellbeing and Technology, Assistive Technology in Social Care, Social Prescribing, Employment, LinkedIn and CV writing, smart cycle lights, digital inclusion and so much more. We have archived the recordings these sessions on the council’s YouTube channel.

Feedback on the Digital Festival Hounslow has been overwhelmingly positive and whilst we can’t include them all here are a couple that really sum the month up for us:

‘This has been a great initiative, and I’m proud to work in an organisation that continuously prides itself in new initiatives and involving colleagues in doing so too. I feel very connected and not isolated (considering when I work remotely (I have no other interactions) which isn’t how it’d be if we were at Hounslow House.’

‘There have been some really great events and the well-being session have had a positive impact, we should have more of these’

This would not have been a success without the work of our partners and the engagement of our community, so we extend a huge thank you from us all to everyone who took part in one way or another.  We will take all we have learned to make next year’s even bigger and better.

Thank you from all of us in the Digital Festival Hounslow team

See you next year!