#tableau charts dataviz | Explore Tumblr posts and blogs

viswatechynology · 3 years ago

Text

R Software

What is R Software?

R is a programming language and free software developed by Ross Ihaka and Robert Gentleman in 1993. R possesses an extensive catalog of statistical and graphical methods. It includes machine learning algorithms, linear regression, time series, statistical inference to name a few. Most of the R libraries are written in R, but for heavy computational tasks, C, C++ and Fortran codes are preferred.

R is not only entrusted by academic, but many large companies also use R programming language, including Uber, Google, Airbnb, Facebook and so on.

Data analysis with R is done in a series of steps; programming, transforming, discovering, modeling and communicate the results

Program: R is a clear and accessible programming tool

Transform: R is made up of a collection of libraries designed specifically for data science

Discover: Investigate the data, refine your hypothesis and analyze them

Model: R provides a wide array of tools to capture the right model for your data

Communicate: Integrate codes, graphs, and outputs to a report with R Markdown or build Shiny apps to share with the world

In this introduction tutorial you will learn R

What is R used for?

R by Industry

R package

Communicate with R

Why use R?

Should you choose R?

Is R difficult?

What is R used for?

Statistical inference

Data analysis

Machine learning algorithm

R by Industry :

If we break down the use of R by industry, we see that academics come first. R is a language to do statistic. R is the first choice in the healthcare industry, followed by government and consulting.

R package

The primary uses of R is and will always be, statistic, visualization, and machine learning. The picture below shows which R package got the most questions in Stack Overflow. In the top 10, most of them are related to the workflow of a data scientist: data preparation and communicate the results.

All the libraries of R, almost 12k, are stored in CRAN. CRAN is a free and open source. You can download and use the numerous libraries to perform Machine Learning or time series analysis.Communicate with R

R has multiple ways to present and share work, either through a markdown document or a shiny app. Everything can be hosted in Rpub, GitHub or the business’s website. Rstudio accepts markdown to write a document. You can export the documents in different formats:

Document :

· HTML

· PDF/Latex

· Word

Presentation :

· HTML

· PDF beamer

Why use R?

Data science is shaping the way companies run their businesses. Without a doubt, staying away from Artificial Intelligence and Machine will lead the company to fail. The big question is which tool/language should you use?

They are plenty of tools available in the market to perform data analysis. Learning a new language requires some time investment. The picture below depicts the learning curve compared to the business capability a language offers. The negative relationship implies that there is no free lunch. If you want to give the best insight from the data, then you need to spend some time learning the appropriate tool, which is R.

On the top left of the graph, you can see Excel and PowerBI. These two tools are simple to learn but don’t offer outstanding business capability, especially in term of modeling. In the middle, you can see Python and SAS. SAS is a dedicated tool to run a statistical analysis for business, but it is not free. SAS is a click and run software. Python, however, is a language with a monotonous learning curve. Python is a fantastic tool to deploy Machine Learning and AI but lacks communication features. With an identical learning curve, R is a good trade-off between implementation and data analysis.

When it comes to data visualization (DataViz), you’d probably heard about Tableau. Tableau is, without a doubt, a great tool to discover patterns through graphs and charts. Besides, learning Tableau is not time-consuming. One big problem with data visualization is you might end up never finding a pattern or just create plenty of useless charts. Tableau is a good tool for quick visualization of the data or Business Intelligence. When it comes to statistics and decision-making tool, R is more appropriate.

Stack Overflow is a big community for programming languages. If you have a coding issue or need to understand a model, Stack Overflow is here to help. Over the year, the percentage of question-views has increased sharply for R compared to the other languages. This trend is of course highly correlated with the booming age of data science but, it reflects the demand of R language for data science.

In data science, there are two tools competing with each other. R and Python are probably the programming language that defines data science.

Should you choose R?

Data scientist can use two excellent tools: R and Python. You may not have time to learn them both, especially if you get started to learn data science. Learning statistical modeling and algorithm is far more important than to learn a programming language. A programming language is a tool to compute and communicate your discovery. The most important task in data science is the way you deal with the data: import, clean, prep, feature engineering, feature selection. This should be your primary focus. If you are trying to learn R and Python at the same time without a solid background in statistics, its plain stupid. Data scientist are not programmers. Their job is to understand the data, manipulate it and expose the best approach. If you are thinking about which language to learn, let’s see which language is the most appropriate for you.

The principal audience for data science is business professional. In the business, one big implication is communication. There are many ways to communicate: report, web app, dashboard. You need a tool that does all this together.

Is R difficult?

Years ago, R was a difficult language to master. The language was confusing and not as structured as the other programming tools. To overcome this major issue, Hadley Wickham developed a collection of packages called tidyverse. The rule of the game changed for the best. Data manipulation become trivial and intuitive. Creating a graph was not so difficult anymore.

The best algorithms for machine learning can be implemented with R. Packages like Keras and TensorFlow allow to create high-end machine learning technique. R also has a package to perform Xgboost, one the best algorithm for Kaggle competition.

R can communicate with the other language. It is possible to call Python, Java, C++ in R. The world of big data is also accessible to R. You can connect R with different databases like Spark or Hadoop.

Finally, R has evolved and allowed parallelizing operation to speed up the computation. In fact, R was criticized for using only one CPU at a time. The parallel package lets you to perform tasks in different cores of the machine.

Summary

In a nutshell, R is a great tool to explore and investigate the data. Elaborate analysis like clustering, correlation, and data reduction are done with R. This is the most crucial part, without a good feature engineering and model, the deployment of the machine learning will not give meaningful results.

#what is R Software #explain R Proghrmming #R Software

2 notes · View notes

warninggraphiccontent · 5 years ago

Text

20 November 2020

Some personal news

Funny how whenever anyone says they have 'some personal news', it's always professional news, isn't it?

It was my turn yesterday. After more than seven years at the Institute for Government, I've decided it's time for a new challenge. I'll be going freelance from 1 January, so please get in touch if you'd like to work with me (all interesting projects on data, digital, openness, government, etc considered). I'll also be working on a book idea. Exciting, if also a little bit vaguely terrifying...

I'll still be an associate at the IfG, and still running our Data Bites event series. (Put Wednesday 2 December in your diary for the next one, and then Wednesday 3 February 2021 after that.)

And - rest assured! - I'll still be writing this newsletter, though it will be taking a break for much of December.

Just one more thing this week: I have a report out (with colleagues Marcus and Oliver) on digital government (in the UK) during the coronavirus crisis. There's a nice write-up from diginomica here, some nice quotes for the paperback from Tanya Filer and Tom Loosemore, and I'll be on the IfG podcast talking about it later. I'm a big fan of this chart, which tells the story of the crisis through visitors to GOV.UK.

This is the second of three reports on digital government we're publishing this autumn - the first was on policy making in a digital world, and the third, on future technology and the government workforce, will be out soon.

Have a great weekend

Gavin

Enjoying Warning: Graphic Content?

Tell your friends - forward this email, and they can:

Subscribe via email

Follow on Twitter

Follow on Tumblr

Or:

Buy me a coffee (thank you!)

Follow me, Gavin Freeguard, on Twitter

Visit my website

Today's links:

Graphic content

Viral content

3D Map of COVID Cases by Population, March through Today (r/dataisbeautiful)

Covid in the U.S.: Latest Map and Case Count* (New York Times)

Here’s a quick thread on what we changed and why (Charlie Smart)

Visualizing Covid-19 Deaths As Spheres in a Tank (r/dataisbeautiful)

Why rich countries are so vulnerable to covid-19* (The Economist)

COVID wriggling its way up county by county, subsiding, and then returning in six dimensions (Benjamin Schmidt)

States That Imposed Few Restrictions Now Have the Worst Outbreaks* (New York Times)

Coronavirus: Inside test-and-trace - how the 'world beater' went wrong (BBC News)

How have COVID-19 rates changed over the last week in England's small areas? (Carl Baker)

New York and the crisis in mass transit systems* (FT)

The kids aren’t alright: How Generation Covid is losing out* (FT)

The vaccines come of age

An effective covid-19 vaccine is a turning point in the pandemic* (The Economist)

Eurozone economy: the struggle to stay afloat until a vaccine arrives* (FT)

The world will soon have covid-19 vaccines. Will people have the jabs?* (The Economist)

Tracking the vaccine race (Reuters)

A man for Four Seasons

Even in Defeat, Trump Found New Voters Across the U.S.* (New York Times)

How Trump’s presidency turned off some Republicans – a visual guide (The Guardian)

Counties That Suffered Higher Unemployment Rates Voted for Biden* (New York Times)

In 2020, the critical must-win states were the 'blue wall'. By 2024, they could be Arizona, Georgia or even Texas (Aron)

Suburban turnout pushed Joe Biden to victory* (FT)

How Suburbs Swung the 2020 Election (Bloomberg CityLab)

Here’s how long it could take to certify the vote in key states — and the GOP efforts to upend that process* (Washington Post)

#dataviz

#ElectionViz: US TV networks have room for data storytelling improvement (Tableau)

Tracking the US election results: 'We needed to be clear, fast, and accurate' (The Guardian)

Sport and leisure

Lewis Hamilton's seventh F1 world title: The stats (BBC Sport)

How new swing techniques are revolutionising golf* (The Economist)

“The Queen’s Gambit” is right: young chess stars always usurp the old* (The Economist)

Who’s in the Crossword? (The Pudding)

Everything else

The State of Ageing in 2020 (Centre for Ageing Better)

Skyscrapers in London: Do we want to reach for the stars?* (The Times)

Atlas of Sustainable Development Goals 2020 (World Bank)

Boeing’s Max jet set to return just as customers head for exit* (FT)

Behind the tally, names and lives* (Washington Post)

Climate graphic of the week: Siberia experiences record temperatures* (FT)

Meta data

Viral content

Digital government during the coronavirus crisis (IfG)

What has digital government in the UK learned during the COVID-19 crisis? (diginomica)

Investigation into government procurement during the COVID-19 pandemic (NAO)

How DWP managed a surge in demand for Universal Credit during COVID-19 (diginomica)

Vaccine rumours debunked: Microchips, 'altered DNA' and more (BBC News)

Health

Crowdsourcing Our NHS AI Lab Skunkworks Project (NHSX)

Working on a global mental health databank pilot (Wellcome Digital)

National project shows digital inclusion is key to tackling health inequalities (Good Things Foundation)

UK government

The National Data Strategy for Health and Care (and the other one for everything else) (medConfidential)

The UK National Data Strategy 2020: doing data ethically (ODI)

Matt Warman's speech on digital identity at Identity Week 2020 (DCMS)

Integrated Review (the Prime Minister)

The latest release of @ONSgeography's National Statistics UPRN Lookup links #UPRNs to postcodes (via Owen Boswarva)

The Document Checking Service: trialling online passport validity checks (Government Digital Service)

A possible expansion of FOIA... (via George Greenwood)

Taiwan

How Taiwan beat Covid-19* (Wired)

Taiwan’s civic tech gift to the world (GovInsider)

How Taiwan became a coronavirus success story (IfG, from June 2020)

North America

Data disappeared: four years of the Trump administration (Highline)

How the U.S. Military Buys Location Data from Ordinary Apps (Motherboard)

The federal government’s chief information security officer is helping an outside effort to hunt for alleged voter fraud* (Washington Post, via Alice)

Zuckerberg and Dorsey to be quizzed by Senate following Biden vote victory (BBC News)

Companies could face hefty fines under new Canadian privacy law (CBC)

Analysis (Cory Doctorow)

Everything else

Announcing the Data Collective: Free training, consultancy, peer support, and community for those using data in the social sector (DataKind UK)

Increasingly trusted to find an edge: What it’s like to be a club’s data analyst* (The Athletic)

Design is the strategy* (Apolitical)

An adequacy determination does not resolve the lower standard of data protection in the UK. (Amberhawk)

The TBI Globalism Study: Transparency and Autonomy Should Underpin Online Voting Systems (Tony Blair Institute for Global Change)

The Data Governance Working Group of the Global Partnership for AI is seeking feedback on how we're thinking about our work and scope (via Jeni)

Opportunities

JOB: Director, GOV.UK (GDS)

JOB: Head of Technology and Architecture for GOV.UK opening at GDS (Technology in Government)

COURSE: ANNOUNCING: First of its Kind Executive Course on Data Stewardship — Focused on Data Re-Use in the Public Interest (Open Data Policy Lab)

EVENT: How to enhance the UK’s geospatial ecosystem (Geospatial Commission)

EVENT: UKGovCamp 2021

And finally...

The R number, crocheted. (Statistrikk)

The Civic Tech Graveyard

AI can now produce passable parody song lyrics. The system is called Weird AI Yankovic. Really. (Pando)

1 note · View note

viswatech · 3 years ago

Text

R-PROGRAMMING LANGUAGE

What is R Language?

R is not only entrusted by academic, but many large companies also use R programming language, including Uber, Google, Airbnb, Facebook and so on.

Data analysis with R is done in a series of steps; programming, transforming, discovering, modeling and communicate the results

Program: R is a clear and accessible programming tool

Transform: R is made up of a collection of libraries designed specifically for data science

Discover: Investigate the data, refine your hypothesis and analyze them

Model: R provides a wide array of tools to capture the right model for your data

Communicate: Integrate codes, graphs, and outputs to a report with R Markdown or build Shiny apps to share with the world

In this introduction tutorial you will learn R

What is R used for?

R by Industry

R package

Communicate with R

Why use R?

Should you choose R?

Is R difficult?

What is R used for?

Statistical inference

Data analysis

Machine learning algorithm

R by Industry

If we break down the use of R by industry, we see that academics come first. R is a language to do statistic. R is the first choice in the healthcare industry, followed by government and consulting.

R package

Communicate with R

Document :

· HTML

· PDF/Latex

· Word

Presentation

· HTML

· PDF beamer

Why use R?

In data science, there are two tools competing with each other. R and Python are probably the programming language that defines data science.

Should you choose R?

Is R difficult?

Summary

#Rlanguage Rprogramming explainrlanguage

1 note · View note

charlenejpatterson · 7 years ago

Text

Dataviz: A Critical Skill for Modern Marketers

A decade ago a friend bought me a copy of Edward Tufte’s iconic book Beautiful Evidence.

The professor emeritus of political science, statistics, and computer science at Yale University has spent his career teaching others how to turn information and data into elegantly crafted drawings and graphics – and even more, doing so in a way that illuminates in interesting and unexpected ways.

Inspired by him, I set out to learn more about visualizing data, and how to use it in everyday life. The subject area is massive and at times overwhelming, but data visualization (sometimes called “dataviz”) is among the most critical skills for marketers to understand at least at the basic level, if not to study in more depth. Let’s walk through the what, how, and why of data visualization for marketing.

HANDPICKED RELATED CONTENT: Building Your Content Marketing Team? 14 Skills for New, Growing, and Mature Programs

What’s data visualization?

Put simply, dataviz is the art and science of displaying information (data) in visual form. While bar charts are a form of dataviz, the term is more often used to describe the translation of complex or nuanced data into summarizing, artful images. One of the most highly rated sessions at Content Marketing World was from Scott Berinato, senior editor at the Harvard Business Review and author of Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations. In an interview with CCO magazine, Scott explains that in today’s data-abundant world, finding ways to extract human insights from data is a key challenge (and critical skill):

Finding ways to extract human insights from data is a critical skill, says @scottberinato. #dataviz Click To Tweet

“The amount of information coming at us is insane. It’s overwhelming. So visualization serves two purposes. First, it serves a prosaic purpose. It gets people’s attention … When you’re fighting for attention, whether in a Twitter feed or even in a presentation, visuals work …

“Second, it solves the problem of relaying complex information. Consider something as simple as trying to understand the gun debate in America. There are so many people saying so many things about guns. Visualization is a way of making sense of all the data, ideas, and information.”

What’s the application for marketers?

Let’s explore two practical and easy-to-understand ways marketers use dataviz as well as real-world cases showing how it’s applied.

Dataviz as marketing insight

The scenario Scott explains – living at a time of data abundance – is particularly true for marketers. Whether we are reviewing our analytics platforms, mining user data for insights, or reviewing sales performance to understand what variables are driving (or dampening) growth, visualizing this information is critical to make sense of what can be overwhelming detail.

Among the most interesting examples I’ve read of late is a case study published by Tableau (the data visualization software company) about its work with outdoor retailer REI. (You can read the full case here.) Managers across REI visualize owned data – online and in-store transactions, operations information, buyer demographics, etc. – to extract insights and improve customer experience.

What used to be done inelegantly with Excel is now visualized instantly using Tableau dashboards. And because Tableau lets you interrogate the data and visualize findings – sorting, slicing, and filtering in real time – it is more likely to surface interesting and unexpected findings. (No more static decks with a single view chosen by the presenter.)

HANDPICKED RELATED CONTENT: Data-Driven Content Strategy Meets Content Marketing [Essential Template]

Dataviz as content

Maybe you’re curious about using marketing data, but deep marketing analytics is a step beyond what you’re interested in? The use case nearest to my heart is publishing data as content marketing. Research can take many forms. Some companies host surveys to gather insights about their industries (salary guides and “state of” reports come to mind). Others analyze third-party data (such as public datasets or licensed data) to uncover new ideas or create interesting infographics. And still others find that their internal data can generate interesting lessons to share.

My favorite examples take their original research and make it sing using strong data visualizations to present findings. Among my recent favorites:

Take original research and make it sing using strong #data visualizations to present findings, says @clare_mcd. Click To Tweet

Salesforce does a nice job with its research efforts in large part because of the strict information design that underlies each publication. Charts and graphs are clean and easy to understand. Rather than simply restating research findings, Salesforce explains its point of view on key issues affecting the industry. Salesforce’s AI Revolution report is a great example of its design ethic.

Not every viz needs to be a serious exercise in thought leadership. The avocado toast index is a great example of using existing data in a new and hilarious way.

Not every viz of #data needs to be a serious exercise. @BBC avocado toast index is great example. @clare_mcd Click To Tweet

Most helpful tips for dataviz

Let’s be frank. Learning how to visualize data is a massive subject that you could spend years refining and finessing. Rather than trying to sum up a complex discipline, I’ll give the basics that will be most helpful:

Clarity not cleverness

This is the biggest lesson of all. Great data visualization isn’t fussy or ornate. With so many tools that make it easy for marketers to visualize data, there’s a tendency to let “cool” win out over the simple stuff. Don’t fall for it. Simplicity is much more credible and appreciated than overly ornate (and opaque) visualizations.

Great data visualization isn’t fussy or ornate, says @clare_mcd. #dataviz Read more>> Click To Tweet

Ask “so what?”

One newbie mistake is the desire to publish every finding from a survey though your reader doesn’t have the interest or attention for it. For each dataviz, you should be able to answer the question, “So what?” Why does this point matter? How does it add to my story? (Plus, loading your report with dozens of data graphics is expensive.)

Guide the eye

Sometimes your readers need a gentle nudge. Where should they be looking? What data point in your chart is most important? Consider adding guides to your dataviz to point out which finding is interesting or what gap is most surprising. These little hints – if used sparingly – are helpful to those encountering your viz for the first time.

HANDPICKED RELATED CONTENT: 5 Important Visual Lessons From Designers for Content Marketers

Use color wisely

Color should not be decorative; it should be clarifying. Unless you are using colors to distinguish categories, do not use more than one color (or a single-color palette). For example, if you’re presenting a bar chart where one data point (i.e., bar) is most interesting, make that bar your primary color and gray the other bars so they recede to the background. These visual cues help your viewer focus on what matters.

The chart from Udemy uses multiple colors, but it uses them to distinguish among generations – a good use case.

The chart from The Wall Street Journal highlights huge box office sales for Black Panther by showing that film in red, and using a light blue for all other data points. Doing this ensures that the reader knows where to look on a relatively “busy” visual.

‘Black Panther’ has become one of the most successful movies ever in a near-record amount of time, completely dominating the winter box office in the process https://t.co/l4MQtMOgSu pic.twitter.com/aCu1I2xyZx

— WSJ Graphics (@WSJGraphics) April 1, 2018

https://platform.twitter.com/widgets.js

Choose chart types carefully

The pie chart is a popular choice to visualize percentages that add up to 100%, but it’s often not the optimal choice. Beyond a few slices, it’s hard to compare the relative size of each section. Bar charts are the workhorses of dataviz for good reason (for a longer list of variables, horizontal bar charts often work better).

Departing from pie charts and bar charts, there are amazing chart types to explore. My personal favorite is the Sankey Diagram.

After Ebola outbreak in West Africa, donors pledged $4.5 billion toward recovery. Less than a third of that money has been disbursed. Graphic by @JoelEastwood https://t.co/xbucKqbVdV pic.twitter.com/IWMg7K5MNb

— WSJ Graphics (@WSJGraphics) March 20, 2018

https://platform.twitter.com/widgets.js

If you’re stumped about which chart/graph to use, you may find this guide helpful.

Pie charts are popular but often not the optimal choice. Bar charts are workhorses for #dataviz. @clare_mcd Click To Tweet

To prove that smart people prefer simple data visualizations, check out the annual blogger survey from Orbit Media’s Andy Crestodina. He uses simple, horizontal bar charts to convey his findings every year.

HANDPICKED RELATED CONTENT: 6 Mistakes Ruining Your Charts and Infographics

Consider interactive

Some of the most interesting visualizations are interactive, meaning the viewer can filter the data in new ways or uncover layers of data below each chart. The option is particularly nice when you have a sample size large enough to support comparisons of multiple dimensions. (For example, if you examine a finding by viewing responses by industry, you can only do that if you have enough people within each industry category to ensure that each data point presented is statistically significant.) Check out the gallery on Tableau Public to see how it works.

HANDPICKED RELATED CONTENT: Interactive Content: The Good, Bad, and Wicked Cool Quizzes and Games

Choose viz technology carefully

The wealth of tech tools to help you visualize is nothing short of freaking amazing. I’ve found, however, that tools designed primarily for layout or design rather than dataviz are usually an exercise in frustration. I have wasted more time fiddling with some of them than I care to admit. What you really want are tools designed specifically for visualizing data, not just visualizing stuff.

Use tools designed for visualizing data, not just visualizing stuff, says @clare_mcd. #dataviz Click To Tweet

According to HBR’s Scott, your most critical tools before using any technology are pen and paper – and he’s correct. (His book spends a good deal of time talking about sketching out ideas and how to choose chart types, my favorite part of the book.)

With a sketch as your guide, for basic visualizations I recommend Plotly or Datawrapper. (Good ol’ Excel is another option though it frustrates me quickly.) Scott also recommends Quadrigram, though I have not used it. Another tool I’m eager to try: Google Data Studio.

For more advanced visualizations, Tableau is an amazingly powerful option suited to intermediate or advanced users.

Of course, tools need data to make the magic. You can access both free and paid datasets through a variety of communities and companies. Through some sites, you’ll find relatively clean data ready to visualize, while others require developer skills to query and clean. To understand what’s available, scan through communities like Kaggle, Google Public Data, and Github Data. And, if you have the budget, you can license an array of data. A great example is Attom Data Solutions, a repository for property data. (If you’re on the hunt for niche data, the r/datasets community on Reddit is a good place to ask questions.)

Read up before you dive

While you may be inclined to dive in and start experimenting, I recommend pairing your experiments with some reading. For beginners who don’t expect to go far beyond updating presentation decks, I highly recommend The Wall Street Journal’s Guide to Information Graphics. It’s a great primer on the do’s and don’ts of clear, simple viz design. (The book’s lessons about color choices are worth the price.)

For those with more than a passing interest, Scott’s Good Charts is an excellent guide, as is Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic.

If you’re interested in visualizing public data sources, Niel Malhotra from Growista wrote an online guide to research and his chapter about accessing and analyzing existing data is informative. (Niel’s background is programming.)

Finally, one of the most inspiring things you can do is to see what others are doing. I often visit the communities on Tableau, Data is Beautiful (on Reddit), and Information is Beautiful. Another great source of information is following data journalism sites on Twitter, such as @GuardianData, @BBGVisualData, @ReutersGraphics, @GuardianVisuals, @NYTGraphics, and @WSJGraphics.

Last, but not least, have fun with dataviz.

Please note: All tools included in our blog posts are suggested by authors. No one post can provide all relevant tools in the space. Feel free to include additional tools in the comments (from your company or ones that you have used).

Learn more from Clare McDermott and her research-related insight as she presents at Content Marketing World Sept. 4-7 in Cleveland, Ohio. Register today and use code BLOG100 to save $100.

Cover image by Joseph Kalinowski/Content Marketing Institute

The post Dataviz: A Critical Skill for Modern Marketers appeared first on Content Marketing Institute.

0 notes

lucyariablog · 7 years ago

Text

Dataviz: A Critical Skill for Modern Marketers

A decade ago a friend bought me a copy of Edward Tufte’s iconic book Beautiful Evidence.

HANDPICKED RELATED CONTENT: Building Your Content Marketing Team? 14 Skills for New, Growing, and Mature Programs

What’s data visualization?

Finding ways to extract human insights from data is a critical skill, says @scottberinato. #dataviz Click To Tweet

What’s the application for marketers?

Let’s explore two practical and easy-to-understand ways marketers use dataviz as well as real-world cases showing how it’s applied.

Dataviz as marketing insight

HANDPICKED RELATED CONTENT: Data-Driven Content Strategy Meets Content Marketing [Essential Template]

Dataviz as content

My favorite examples take their original research and make it sing using strong data visualizations to present findings. Among my recent favorites:

Take original research and make it sing using strong #data visualizations to present findings, says @clare_mcd. Click To Tweet

Not every viz needs to be a serious exercise in thought leadership. The avocado toast index is a great example of using existing data in a new and hilarious way.

Not every viz of #data needs to be a serious exercise. @BBC avocado toast index is great example. @clare_mcd Click To Tweet

Most helpful tips for dataviz

Clarity not cleverness

Great data visualization isn’t fussy or ornate, says @clare_mcd. #dataviz Read more>> Click To Tweet

Ask “so what?”

Guide the eye

HANDPICKED RELATED CONTENT: 5 Important Visual Lessons From Designers for Content Marketers

Use color wisely

The chart from Udemy uses multiple colors, but it uses them to distinguish among generations – a good use case.

— WSJ Graphics (@WSJGraphics) April 1, 2018

Choose chart types carefully

Departing from pie charts and bar charts, there are amazing chart types to explore. My personal favorite is the Sankey Diagram.

— WSJ Graphics (@WSJGraphics) March 20, 2018

If you’re stumped about which chart/graph to use, you may find this guide helpful.

Pie charts are popular but often not the optimal choice. Bar charts are workhorses for #dataviz. @clare_mcd Click To Tweet

HANDPICKED RELATED CONTENT: 6 Mistakes Ruining Your Charts and Infographics

Consider interactive

HANDPICKED RELATED CONTENT: Interactive Content: The Good, Bad, and Wicked Cool Quizzes and Games

Choose viz technology carefully

Use tools designed for visualizing data, not just visualizing stuff, says @clare_mcd. #dataviz Click To Tweet

For more advanced visualizations, Tableau is an amazingly powerful option suited to intermediate or advanced users.

Read up before you dive

Last, but not least, have fun with dataviz.

Learn more from Clare McDermott and her research-related insight as she presents at Content Marketing World Sept. 4-7 in Cleveland, Ohio. Register today and use code BLOG100 to save $100.

Cover image by Joseph Kalinowski/Content Marketing Institute

The post Dataviz: A Critical Skill for Modern Marketers appeared first on Content Marketing Institute.

from http://contentmarketinginstitute.com/2018/04/dataviz-skill-marketers/

0 notes

dustydata · 9 years ago

Text

Charts IRL

Hey Peeps! I’m back after a bit of time off the blog scene. It’s been a crazy few weeks since the conference and between work, family, and getting the flu/pink eye (see family...) I didn’t have a whole lot of time to put pen to paper....er mouse to tableau? Anyway, I was thinking alot about what I wanted to do next with this blog. I wanted to start up a new series for 2017 that would be:

- Interesting

- Not SUPER time consuming (see work / family)

- Let me do some fun stuff in Tableau and learn a little

So, with that in mind and after a few of my patented “shower idea sessions” I came up with “Charts In Real Life”. I changed it to Charts IRL to be hip/cool with the kids nowadays :). There are only a few rules to this new project:

1) Each Charts IRL needs to be inspired by something I see IRL (in real life)

2) The dashboard work itself can’t take me more than 1 hour

3) The data doesn’t have to be super clean, just something that works

and that’s pretty much it! Let’s dive into the first CIRL!

Charts IRL 1

Inspiration - Actually the first Charts IRL came directly from my shower session. I stepped out of the shower one day and was like “wow, that would be a sweet Tableau color palette” - HA “what a nerd!” I thought....but seriously, nice colors - check it out below.

So with that I started. The first thing I did was pull the colors, which I did with my handy dandy PowerPoint picker skills (yeah, I know Tableau has a picker, but I do a bunch of stuff in PP, so I figured why not).

These are the ones I came up with, of course with pictures there are a lot of different colors that can come up, but i went with ones that made sense saturation-wise.

Next, I wanted something to pull some data off of, so I figured “why don’t I just see where these things were made?”

OK - looks like my 3 towels were made in 3 different countries! Awesome, that will work well with my new color palette! Pink - Turkey, Mustard - Pakistan, Blue - India.

Interwebs - The next thing I did was was about 25 minutes trying to find textile import data with historical records....yeah apparently not super easy to find without paying for it, so I ended up defaulting to GDP data and some high level import/export stats from this site https://ustr.gov/countries-regions (the government!)

Next up, the dashboard! With only about an hour to do this (really was on a time clock here - Cal went down for his mid-day nap and it felt like I was 10 again playing PERFECTION, trying to get everything in the right spot before it popped off the board!

Nostalgia pic

Dashboard

I split my dashboard into 3 main bars

Bar 1 - Listing the 3 countries out with the images of my towel tags and some detail on import/exports. This was achieved with a horizontal container and some text boxes

Bar 2 - Floating image of my towels overlaid on a map. I made some sweet chevron arrow lines in powerpoint and floated them over the map to make it a little more interesting and layered in some gdp data in the tooltips of the map. Additionally, I did the trick where you make separate fields for each dimension name (else null) and color them in the tooltip so all the colors matched nicely.

Bar 3 - A parameterized bubble time chart which displayed either GDP % change or GDP dollars. I went with bubbles because they looked neat, pretty much it :). I added the parameter selector in the top right to make it easy to change out.

And that’s it! Nothing too crazy, but a fun way to start connecting real life with Tableau, it’s more fun when I at least semi-care about the data I’m visualizing!

I hope you guys like CIRL, one of the new projects for 2017 that I am starting up! More to come, it’s going to be an awesome year!

https://public.tableau.com/profile/dustiboy21#!/vizhome/ChartsIRL1/ChartsIRL1-Towels

Dustin

#tableau charts dataviz

0 notes

warninggraphiccontent · 5 years ago

Text

17 April 2020

Let's get quizzical; or, is that your final anecdote?

The ITV drama Quiz, all about Major Charles Ingram's appearance on Who Wants To Be A Millionaire?, has brought back some memories. I ended up discussing my time on the show with the Daily Mail podcast yesterday (29:12 in).

I'm told my appearance has resurfaced on YouTube (though you really need to watch Rob Mitchell, the contestant before me, to get a full flavour of the tension that night), but why not test yourself against the Major's route to the million here.

Elsewhere, a big thank you to Giuseppe for mentioning our Data Bites report in his newsletter - read the report here, watch the events here, keep 6pm on Wednesday 6 May free for the next one - and to Stefan for his kind comments about this newsletter. (Please tell your friends to subscribe, follow, etc.)

And I'll have something on the IfG website at some point about personal data and coronavirus, held up by me delivering virtual data training yesterday and today (which may actually have worked better online than it does in person...).

Have a good weekend

Gavin

Today's links:

Tips and tech, etc

Responding to coronavirus: how dedicated staff and volunteers are transforming our service (Citizens Advice)

Working from home has a troubled history. Coronavirus is exposing its flaws again (The Guardian)

Here's my five-step guide to appearing on TV programmes via Skype or Facetime (Jeremy Vine)

This is no time to sleep late (Rachel Coldicutt)

Strange (First) Days (Matt Jukes)

Graphic content

Viral content

This 3-D Simulation Shows Why Social Distancing Is So Important* (New York Times)

Coronavirus tracked: the latest figures as the pandemic spreads (FT - and thread)

Tracking covid-19 excess deaths across countries* (The Economist)

U.K. Coronavirus Map and Case Count* (New York Times)

When the Coronavirus Outbreak Could Peak in Each U.S. State* (Bloomberg)

Covid-19 is rapidly becoming America’s leading cause of death* (Washington Post)

UK public largely follows lockdown rules — except for Easter break* (FT)

Sheltering in small places: What life indoors looks like in Tokyo’s cramped homes (Reuters)

New confirmed COVID-19 deaths (Jo Michell, via Daniel)

Change in tons of household waste collected, March 2020 vs. March 2019 (The City)

Dashboards... (via Phil Booth)

Some fresh analysis of the factors that do — and do not — appear to influence the pace of countries’ covid-19 outbreaks (John Burn-Murdoch)

The Coronavirus Death Toll Is Rising At Different Rates In Different Countries. These Charts Help Explain Why. (BuzzFeed)

For those still wondering how far off the scale UK deaths are compared with a normal flu epidemic (Chris Giles)

Viral content: consequences

YouGov/Imperial College study examines how well public in 13 countries are responding to COVID-19 (YouGov)

Doing more of what it takes (Resolution Foundation)

How the internet has changed during lockdowns* (The Economist)

Electricity prices slump as businesses close across the US* (FT)

A Gloomy Prediction on How Much Poverty Could Rise* (The Upshot)

Don’t hoard! (Reuters)

How coronavirus stalled climate change momentum* (FT)

How visualizing quantified self data can help you find meaning in a quarantined world (Tableau)

Viral content: #dataviz

Log Graphs (Anthony B. Masters)

Another PHE data disaster (Simon Briscoe)

Is the open data still available? (ODI Leeds)

Reviewing the charts in the Oxford Covid-19 study (Junk Charts)

Anti-viral content

Finally We May Have a Path to the Fundamental Theory of Physics… and It’s Beautiful (Stephen Wolfram)

HS2 (IfG)

Meta data

Viral content: on track?

Coronavirus: Govt set to release 'contact tracking' app which detects nearby virus carriers (Sky News, two weeks ago)

App-based contact tracing may help end coronavirus lockdowns (The Economist)

NHS phone app holds key to lifting UK’s coronavirus lockdown* (Sunday Times)

Coronavirus: phone app will trace every contact of the infected under Big Tech plan* (Sunday Times)

Use of surveillance techniques to beat coronavirus requires public trust* (Sunday Times)

Government to release app to track infections (Civil Service World)

Will Google’s and Apple’s COVID Tracking Plan Protect Privacy? (The Markup)

Can your smartphone crack Covid? (UnHerd)

Automated contact tracing is not a coronavirus panacea (Jason Bay)

Our new dialogue with the public about data for public benefit (National Data Guardian)

UK government using confidential patient data in coronavirus response (The Guardian)

Put privacy first in tech fight against coronavirus (Politico)

Coronavirus triggers soul-searching on privacy in Germany (Politico)

A Closer Look at Location Data: Privacy and Pandemics (Future of Privacy Forum)

THE LIMITS OF LOCATION TRACKING IN AN EPIDEMIC (ACLU)

Apple and Google detail bold and ambitious plan to track COVID-19 at scale (Ars Technica)

NHS in standoff with Apple and Google over coronavirus tracing (The Guardian)

Big data versus COVID-19: opportunities and privacy challenges (Bruegel)

Growth in surveillance may be hard to scale back after pandemic, experts say (The Guardian)

to all the automated contact tracing advocates: South Korea is doing this right... (@halhod)

Viral misinformation

Here’s where those 5G and coronavirus conspiracy theories came from (Full Fact)

Instagram And YouTube Have Been Accused Of "Moral Failure" Over Coronavirus Conspiracy Sales (BuzzFeed)

What Google and Facebook need to do to fight disinformation (CJR)

Viral content: counting the cost

Chair writes to National Statistician on Covid-19 mortality data quality (PACAC, via Alice)

The real severity of the UK’s coronavirus outbreak (BBC Newsnight)

Government has misled public over UK deaths being lower than France (HSJ)

UKSA, the public good and covid19 deaths (Simon Briscoe - also this)

Don’t put too much faith in Covid-19 metrics (UnHerd)

Viral content: consequences

Government urged to delay digital services tax amid coronavirus outbreak (Computer Weekly)

Universal Credit claimants to verify identity through Government Gateway (DWP)

Anti-viral content

Civil society in a digital world (Rachel Coldicutt)

Planned obsolescence: the outrage of our electronic waste mountain (The Guardian)

A lively and enlightening history of the census* (The Economist)

Opportunities

JOB: Data Analyst Graduate (Arriva UK Trains, via Lee)

EVENT: Beyond the exit strategy: ethical uses of data-driven technology in the fight against COVID-19 (Nuffield Council on Bioethics/Ada Lovelace Institute)

COURSE: Want to learn to be a #datajournalist? @AlbertoCairo and I worked on this #MOOC with the great team at @utknightcenter, supported by the @GoogleNewsInit (Simon Rogers)

And finally...

Viral content

A Comic Strip Tour Of The Wild World Of Pandemic Modeling (FiveThirtyEight)

DP-3T contact tracing (Nicky Case)

Anti-viral content

The Infinite Monkey Theorem Experiment (The Pudding)

Bad Bunny, a Puerto Rican Trap King, Is the World’s Biggest Pop Star* (Bloomberg)

our prediction model for the 2020 presidential election is now live (G. Elliott Morris)

0 notes

warninggraphiccontent · 5 years ago

Text

17 January 2020

2020 vision

(Yes, of course I was going to do that eventually. Yes, 2020 hindsight will inevitably be a headline at some point.)

Whitehall Monitor 2020, our flagship report on the size, shape and performance of government, with lots of lovely #dataviz, will be out over the weekend/early next week. More in next week's edition, but we may be able to squeeze you into Tuesday lunchtime's launch event, where - after I outline some of the key conclusions - a brilliant panel will discuss what's in store for government in 2020. Come! Or watch the livestream.

Trending

Yesterday, I took part in a (really enjoyable) launch event for NatCen's new report looking at 50 years of social trends. We touched on optimism (think Our World in Data or the Roslings showing how things have improved globally) versus pessimism (dig beyond the headlines and there are some surprising facts - and, you know, climate change, geopolitics, etc etc etc), long-term policy making and the difficulties of working across government, the need to go beyond aggregated and headline data, and the need for government to just get better at data in the widest sense.

Nice question from former national statistician, Jil Matheson, in response to a mention I made of decision-ready information - how do we get information-ready policy-makers? I'm not sure this recent Ipsos MORI report is hugely encouraging on our prospects... but I think talking about 'data' in a way that makes sense to 'non data people' and conveys its importance, and increasing the political costs of not using information well, are parts of the solution. And I don't think any of us quite knows, yet, how to navigate a transformed information ecosystem around politics and political information.

A second Cummings

Just to add briefly to last week... I don't think it's an earth-shatteringly original prediction to say there'll be a lot of stories about the use and abuse of personal data this year (the New Year Honours 'leak' was a fitting start to 2020 in that respect). But I'm not sure the last few paragraphs of this article, which discuss targeting content at the public (content that 'really engages people') and a unit modelled on the Tory election campaign, are getting quite the attention they deserve. For all the excitement about what could come out of Downing Street on data, we don't have much detail yet. And you may remember the hoohah about data from GOV.UK being used 'to allow targeted and personalised information to be gathered, analysed and fed back actively to support key decision making'.

I wonder (genuine question) if people would feel differently about such data being used to improve the delivery of digital public services versus government using it to target information at people. Many governments are working out the place of government comms in a disintermediated world (decline of gatekeepers like newspapers, governments/corporations/charities etc can communicate directly with the public), but where is the line? As per the joint civil society letter last year, government needs to have conversations about how it uses personal data in public and with the public, otherwise we might squander the opportunity to use such data ethically and intelligently for the public good. </ramble>

Some other points in brief:

Invitations to the first Data Bites of the year will hopefully be going out very soon - for 6pm on Thursday 6 February. (We'll be back to the first Wednesday of the month after that.) Catch up with previous events here.

It's the Masters snooker at Ally Pally this week. I'd almost forgotten I'd played around with some snooker dataviz from last year's world championships. (And if you're wondering why I'm not even attempting any snooker puns, it's because they're all in the post. You have been warned.)

Very sorry not to be at UKGovCamp this weekend, but I hope everyone has a fantastic (and productive) time. I'll be following along here.

And keep an eye out and ears open (and any other body parts in the appropriate position, for that matter) for the latest IfG Inside Briefing podcast later. There will be music. Previous sonifications here.

Have a great weekend

Gavin

Today's links:

Graphic content

Politics and parliament

BAME, LGBT and women MPs by party (Ketaki for IfG - and Peston #GeekoftheWeek)

# of days between laying and approval of each draft affirmative instrument from the 17/19 Parliamentary session (Phil Gorman)

Mapping the Places (House of Commons Library)

Labour leadership and deputy leadership nominations (CLP Nominations, via Tim)

US politics

Who's still in the Democratic presidential race? (Vox, via Ketaki)

How the Democratic Presidential Field Has Narrowed* (New York Times)

Who Won The January Democratic Debate? (FiveThirtyEight)

How map makers will win the 2020 US election* (FT)

Openness

3 Out of 10 UK Government Departments Meeting 2020 Targets for Aid Transparency (Publish What You Fund)

Freedom of Information (Institute for Government)

Environment

2019 Was the Second-Hottest Year Ever, Closing Out the Warmest Decade* (New York Times)

2019 capped world’s hottest decade in recorded history* (Washington Post)

Everything else

The Big Mac index* (The Economist)

Progress and Popularity: Facing the Disillusioned in a New Decade (NatCen)

Global Advisor Predictions (Ipsos MORI)

In charts: Europe’s demographic time-bomb* (FT)

Finding the Worst, Highest-Paid NBA Player, Ever (The Pudding)

The Secret to a Perfect Mari...mekko? (Tableau Fringe Festival)

Meta data

AI and algorithms

Technology Can't Fix Algorithmic Injustice (Boston Review)

Joseph Stiglitz on artificial intelligence: 'We’re going towards a more divided society' (The Guardian)

Ethical algorithm design should guide technology regulation (Brookings)

Beyond Bias: Contextualizing “Ethical AI” Within the History of Exploitation and Innovation in Medical Research (Chelsea Barabas)

Researchers: Are we on the cusp of an ‘AI winter’? (BBC News)

Skillz

How we’re working to transform the way we work with data (Citizens Advice)

It’s a kind of magic… (Government Statistical Service)

Whitehall needs more scientists to compete with China: chief adviser (The Observer)

Global problems need social science (Hetan Shah for Nature)

What Researchers Think About the Culture They Work In (Wellcome)

Evidence

One Year In, the Evidence Act is Producing Results (Nextgov)

Inside the world’s ‘what works’ teams (What Works)

Social media data needed for 'harm' research, say doctors (BBC News)

Everything else

Sadiq Khan calls for evolution of London Datastore (Computer Weekly)

Charting the Next Three Years for OGP (Open Government Partnership)

What if everyone just said 'Nah' to tracking? (The Register)

Microsoft makes 'carbon negative' pledge (BBC News)

Exposing the problem with default data* (FT)

EU considers temporary ban on facial recognition in public spaces* (Politico)

The fourth industrial revolution could lead to a dark future (The Conversation)

MI5 chief sees tech as biggest challenge and opportunity* (FT)

Opportunities

EVENT: What is in store for government this year? Whitehall Monitor 2020 Launch (Institute for Government)

JOB: Policy/Programme Manager - Central Government (techUK)

JOB: Researcher (Social Policy/Public Policy) (Ada Lovelace Institute)

JOB: Senior Analyst (Engage Britain)

JOBS: Senior Quantitative Data Analysts (NatCen)

Introduction to the Data Science Accelerator programme (GDS, GO Science, ONS)

EVENT: Citizen Beta 2020 #26

And finally...

Data

"Oh no it isn't!" "Oh yes it is!" (Andy Riley)

WHAT I LEARNED TRYING TO COPYRIGHT MY OWN FEET (MEL)

Climate, inequality, hunger: which global problems would you fix first? (The Guardian, via Katie)

Reveals the music behind names (Clarallel, via Pritesh)

I got a rather unnerving Rush Hour Crush published in today's Metro. (@shockproofbeats, via Alice)

Viz

Man Leaves Behind 20-Year Career in Finance to Become Photo Manipulation Artist (My Modern Met)

Darth Data (via Duncan Weldon, via Jenny)

Distributions (via Sophie Warnes, via Tim)

0 notes

warninggraphiccontent · 5 years ago

Text

10 July 2020

In-cite-ment

Busy week, so I'll spare you much rambling today. Except a brief rant about having one of our charts tweeted (great!) by a prominent journalist (#impact!) who... went to the trouble of cropping out any attribution (#*@%$!). Something similar has happened to the excellent Our World in Data project in recent weeks, from a Nobel laureate (who seems to have taken the criticism on board) and a leading satirical TV show (who haven't).

Journalists, economists and comedians would be among the loudest to complain if someone did the same to their work. It's easy to cite (it's the internet age - you could even *link*). Certainly easier than making the chart yourself. Good charts are hard to come by and hard work.

Elsewhere:

A couple of government developments that were easy to miss - the future of the Surveillance Camera and Biometrics Commissioners, and a consultation? inquiry? something looking at strengthening communities which has a bit about data at the end.

Congratulations to the winners of this year's Orwell Prizes for political writing!

This is just wonderful.

And I'm not throwing away my shot to include some #dataviz about one of the greatest cultural achievements of the last decade, so its arrival on a certain streaming service is excuse enough. What comes next? Take a look at the And finally.

Have a good weekend

Gavin

Today's links:

Graphic content

Viral content

Britain’s emotional journey through COVID: Impact on wellbeing (Behavioural Insights Team)

Australia places Melbourne under 6-week coronavirus lockdown* (FT)

How the coronavirus pandemic changed mobility habits, by state (Axios)

Tracking the coronavirus across Europe* (The Economist)

Face-off over face-masks: Europe’s latest north-south split* (The Economist)

Six months, six countries, six families — and one unrelenting, unforgiving epidemic* (Washington Post)

What is missing from the online debate around COVID-19 digital tools? (IPR, University of Bath)

“.. we find a positive correlation between levels of [credit-card] activity three weeks ago and the spread of COVID-19 since then.” (J. P. Morgan, via Carl Quintanilla, via Marcus)

The economy

The Recessionals: why coronavirus is another cruel setback for millennials (FT)

Covid-19 Is Bankrupting American Companies at a Relentless Pace* (Bloomberg)

Money really can buy happiness and recessions can take it away* (The Economist)

Easing does it: Economic policy beyond the lockdown (Resolution Foundation)

Charting the Global Economy: Job Worries and Cash Hoarding* (Bloomberg)

Corona shock: July* (Tortoise)

‘It’s a matter of fairness’: squeezing more tax from multinationals* (FT)

Sunak will not be able to play Santa Claus forever* (FT)

UK’s growth rate could be revised after large revisions to official data* (FT)

Banks Are Ditching London Offices and Not Just Because of Covid-19* (Bloomberg)

#BlackLivesMatter

Confederate Statues Were Never Really About Preserving History (FiveThirtyEight)

Black Lives Matter May Be the Largest Movement in U.S. History* (New York Times)

How Much Does Your School Contribute to Segregation? (Urban Institute)

Academics are mapping the legacy of slavery in Britain’s cities (CityMetric)

New census reveals extent of lack of ethnic minority representatives in local councils (The Conversation)

Why Statistics Don’t Capture The Full Extent Of The Systemic Bias In Policing (FiveThirtyEight)

UK government

Permanent secretaries (me for IfG)

Ministerial directions (IfG, being updated shortly - more here)

Infrastructure and Projects Authority annual report 2020 (Infrastructure and Projects Authority - more here)

Departmental spending (House of Commons Scrutiny Unit)

Iron the prize

Ready to take your data skills to the next level? Iron Viz is back for 2020 with our biggest prizes yet (Tableau)

The Design & Thinking Process of my Winning Iron Viz “The Global Journey of Refugees” (Hesham Eissa)

The Process Behind Building a Winning Iron Viz Feeder Dashboard (Lindsey Poulter)

Everything else

How is flooding affecting your community? (The Pudding)

EU settled status applicants exceed official tally* (FT)

Integrity Watch EU – Parliament meetings (Transparency International)

Boohoo comes out fighting after market tears it to shreds* (FT)

Martin Wolf: ‘Democracy will fail if we don’t think as citizens’ (FT)

EU COALITION EXPLORER (ECFR)

UK CIVIL SOCIETY ALMANAC 2020 (NCVO)

WHAT CAN THE UK CIVIL SOCIETY ALMANAC TELL US ABOUT CHARITIES’ CHALLENGES NOW AND IN THE FUTURE? (NCVO)

There was a vote in Russia last week, on making Putin president for life (Arseny Khakhalin)

2020 attention tracker: The Trump policy trap (Axios)

We've seen new records in atmospheric CO2 concentration almost every May, and of course May 2020 is no different (Gregor Aisch)

Meta data

Viral content: testing times

Coronavirus: The inside story of how UK's 'chaotic' testing regime 'broke all the rules' (Sky News)

How government blindfolded frontline public health experts fighting Covid’s next phase (Manchester Evening News)

Central control: why has the government withheld testing data from councils? (The Bureau of Investigative Journalism)

Councils need detailed data to contain Covid-19. Why have they been sidelined? (The Guardian)

Coronavirus: Ireland's Covid Tracker app is out - where's England's? (BBC News)

No date yet for functioning Covid-19 app, DHSC test and trace chief says (Civil Service World)

Viral content: everything else

COVID-19 Report: No green lights, no red lines (Ada Lovelace Institute)

How the coronavirus pandemic is changing social media (Reuters Institute)

Open letter: Reducing barriers to data access for research in the public interest—lessons from covid-19 (BMJ)

COVID-19 and the Digital Divides (Oxford Internet Institute)

DISINFORMATION’S SOCIETAL IMPACT: BRITAIN, COVID, AND BEYOND (Defence Strategic Communications, the official journal of the NATO Strategic Communications Centre of Excellence)

Coronavirus deaths: Taking stock of what we’ve seen so far – and what might happen next (ONS)

Parliamentary votes during COVID-19 (mySociety)

Four lessons the COVID-19 crisis can teach us about data-driven storytelling (World Economic Forum)

AI etc

A Bretton Woods for AI: Ensuring Benefits for Everyone (Rockefeller Foundation)

What can go wrong when governments let algorithms make decisions* (Apolitical)

AI ETHICS: A STRATEGIC COMMUNICATIONS CHALLENGE (Defence Strategic Communications, the official journal of the NATO Strategic Communications Centre of Excellence)

Black Lives Matter shows governments need to rethink their approach to AI and data ethics* (Apolitical)

AI ecosystem in Canada (McGill University)

An online propaganda campaign used AI-generated headshots to create fake journalists (The Verge)

Big tech

The Loss Of Public Goods To Big Tech (Noema)

Apple under pressure to act after TikTok pulls out of Hong Kong (The Guardian)

Civil society news

Finding, building, and retaining data expertise in social accountability organizations (Transparency and Accountability Initiative)

Catherine Stihler to leave Open Knowledge Foundation to lead Creative Commons (Open Knowledge Foundation)

The data unit is one of the teams being lost as part of the BBC England cuts (via Paul Bradshaw)

Government

NaPTAN - the most popular dataset you’ve never heard of (DfT Digital)

ADR UK-sponsored event explores the value of admin data, from Covid-19 responses to a better justice system (ADR UK)

Data Bites 12 (IfG)

GDS 'under duress' - is there a row going on down near Whitechapel? (Computer Weekly)

How secure is government and should we have a right to know? (Public Technology)

Everything else

A new approach to decisions about data (Understanding Patient Data)

Finally! A way to analyse NHS data from 17 million people (UnHerd)

Closing the Data Divide: The Need for Open Data (Microsoft Open Data Campaign)

Is now the time to build a national planning register? (Unboxed)

Goodbye to the Wild Wild Web* (New York Times)

What women can do for data and what data can do for women (Computer Weekly)

Call for Evidence: Technologies for spreading and detecting misinformation (The Royal Society)

Moving online – how ONS is digitising its labour market surveys (ONS)

Opportunities

New job opportunities with GOV.UK at the Government Digital Service (GDS)

JOB: Senior Data Journalist (ONS)

JOB: Senior Data Visualisation Producer (ONS)

JOBS: Senior analysts (Government Data Quality Hub - civil servants only)

JOB: Senior campaigner (Digital Action)

JOB: Program Officer, Thematic Policy Areas (Open Government Partnership)

JOB: Data Analyst & Storyteller (The Data City)

JOB: Communications and Administration Assistant (360Giving)

JOB: Senior Partnerships Manager (ODI)

JOB: GIS Lead Software Developer (Defra)

EVENT: Shaping a post-pandemic future: The role of data and technology in institutional reform (Centre for Progressive Policy)

CONSULTATION: Legislative framework for the governance of common European data spaces (European Commission)

And finally...

Satisfied?

An Interactive Visualization of Every Line in Hamilton (The Pudding)

How does ‘Hamilton,’ the non stop, hip-hop Broadway sensation tap rap's master rhymes to blur musical lines? (Wall Street Journal)

‘Hamilton’ Would Last 4 To 6 Hours If It Were Sung At The Pace Of Other Broadway Shows (FiveThirtyEight)

Food glorious food

If anyone has a recipe site that is Purple, please let me know... (Mark Bradbourne)

What a melon chart this is (via Jon Schwabish)

Sport and leisure

Do Empty Stadiums Affect Outcomes? The Data Says Yes* (New York Times)

Who Did What in Every Agatha Christie Murder Novel* (Bloomberg)

Everything else

Why time feels so weird in 2020 (Reuters)

Venn diagrams* (Tortoise)

Peers need to be reminded to unmute more often than MPs (Giuseppe)

0 notes

warninggraphiccontent · 5 years ago

Text

19 June 2020

Appy talk

GOVERNMENT RUNS PILOT SCHEME, DEVELOPS ALTERNATIVE SOLUTION ALONGSIDE, CHANGES COURSE WHEN TRIAL FINDS FAULTS was surprisingly not one of the headlines heralding the government's abandonment of the original NHSX contact tracing app in favour of closer working with Google and Apple (and not just because no self-respecting sub, outside the New York Times, would run a headline that long, with that many commas).

There are undoubtedly questions for the government to answer - why it was so tempted by tech solutionism at the expense of designing a proper test and trace system; why it made the 'world-beating' app the centrepiece of the banquet before demoting it to a mere cherry on the cake; whether it should have pursued the course it did knowing compatibility with Apple's iOS operating system (and to some extent, Android) could be a problem and whether the UK has lost time as a result; why there wasn't more openness about the Isle of Wight trial; and why the data protection impact assessment for test and trace wasn't completed before the service was rolled out, for a start. And it's obviously not encouraging when the government has already u-turned a dizzying number of times in recent days and weeks.

But for all the justified questions and criticisms, some of the government's critics are being somewhat disingenuous. The trade-offs between centralised (as originally pursued by NHSX) and decentralised (Google/Apple) approaches are more nuanced than is being allowed; the UK is not alone in facing problems rolling out an app; and there are some rather big debates to be had about the respective power of democratic governments and technology companies.

In its statement yesterday, the Department of Health and Social Care claimed that their tests had also found problems with the Google/Apple approach (specifically, how well that solution could measure the distance between devices), and they're not the only ones, which points to a more fundamental question: will any of the proposed apps work?

This hasn't really been done before. The Ada Lovelace Institute said at the start of the crisis that there was 'an absence of evidence to support the immediate national deployment' of mooted technological solutions, including contact tracing apps. Has that changed? Can anyone yet point to a country where a contact tracing app has been shown to have worked? Where an app has been a substitute for (or even a significant part of) a well-designed, broader test and trace system and other measures? Whether the UK public would tolerate some of the infringements on privacy associated with tech-based approaches in some other countries?

Given the situation, a change in approach is welcome and sensible. Continuing down this track (as it were) risked damaging public confidence in the system, and it is vital that government maintains public confidence and earns public trust, especially when it comes to how it uses our data. The Centre for Data Ethics and Innovation put it well when it said its role was to ensure that 'the speed at which innovation must move doesn’t demand that the values of transparency, privacy, scrutiny and good governance are foregone - compromising the public’s trust in public sector innovation longer term'.

Getting it wrong could have long-term consequences. But let's not pretend getting it right is going to be easy.

Three more things:

I've written a comment piece on the prime minister's call for a new cross-government commission on racial inequality. Maybe start with implementing the recommendations of previous inquiries and follow previous initiatives (including some data-related ones)? And if not, at least give us some more details on what it will look like and what it's trying to achieve, and pledge that its recommendations will be adopted?

The winners of this year's Orwell Prizes will be announced on 9 July. Catch up on the shortlists in the meantime.

And details of the next Data Bites will be going live here very, very soon. See you at 6pm on Wednesday 1 July. Previous events here.

Have a good weekend

Gavin

Today's links:

Tips and tech

Lessons learned from organising the first ever virtual csv,conf (Open Knowledge Foundation)

EXPERIENCES OF FACILITATING ONLINE: INNOVATING, ADJUSTING AND KEEPING THINGS THE SAME (Involve)

Graphic content

Viral content

3 months of a global pandemic (Citizens Advice)

I've mapped Google's excellent mobility data (Dan Cookson)

A warning from South Korea: the ‘fantasy’ of returning to normal life (FT)

You Regress It: Have Masks Prevented 66,000 Infections in New York City? (roadtolarissa)

Brexit Heartlands Pay the Highest Price for Coronavirus* (Bloomberg)

Visualizing COVID-19 (Graphicacy)

Much of the world thinks the response to the pandemic has been poor* (The Economist)

What could a physically distanced UK look like after lockdown? (The Guardian)

When the Coronavirus Outbreak Could Peak in Each U.S. State* (Bloomberg)

Poverty and populism put Latin America at the centre of pandemic* (FT)

Pandemic Travel Patterns Hint at Our Urban Future* (Bloomberg)

Viral content: economic consequences

UK GDP - animated version (Henry Lau)

English shoppers’ return points to a gradual retail recovery* (FT)

How many charity employees have been furloughed? (David Kane)

Four conclusions from latest UK labour market data* (FT)

The geography of the COVID-19 crisis in England (IFS)

#BlackLivesMatter

Black Lives Matter protests prompt millions to search online for race history facts* (The Times)

Unemployment Tracker: Job Losses for Black Workers Are Deepening* (New York Times)

YOU KNOW KAREN (The Pudding)

Cities Grew Safer. Police Budgets Kept Growing.* (The Upshot)

The systemic racism black Americans face, explained in 9 charts (Vox)

Exclusive: Top British firms to pay compensation over founders' slavery links* (Telegraph)

UK politics

Keir Starmer scores the highest satisfaction ratings *ever* of an opposition leader on record (Dylan Spielman, Ipsos MORI, via Lee, Tim and Marcus)

Covid could do for Johnson what the snap election did for May (Matt Smith)

The other reason the government U-turned on free school meals* (New Statesman)

UK government

DfID/FCO merger (IfG - bit more here)

Being updated imminently: civil service staff numbers, freedom of information (IfG)

Ministerial directions (IfG)

US politics

America’s anachronistic electoral college gives Republicans an edge* (The Economist)

Wall Street takes aim at Alexandria Ocasio-Cortez in party primary* (FT)

House of Lords: Virtual sittings, participation and Covid-19 (House of Lords Library)

Environment

Emissions Are Surging Back as Countries and States Reopen* (New York Times)

Can India chart a low-carbon future? The world might depend on it.* (Washington Post)

Mean annual temperature for Northern Ireland (Department of Agriculture, Environmental and Rural Affairs)

Sport

FootballGeek

Fight for fourth? Data reveals it will be long road for Manchester United* (The Times)

Everything else

Country & Product Complexity Rankings (Atlas of Economic Complexity)

The unluckiest generation in U.S. history* (Washington Post)

Mark Duggan police shooting: can forensic tech cast doubt on official report? (The Guardian)

Fighting in the Sahel has forced 1.7m people from their homes* (The Economist)

Digital News Report 2020 (Reuters Institute)

Leftwing voters lead decline in trust in UK news media (The Guardian)

#dataviz

Truncating the axis (Chad Skelton and others)

Infographics (Government Statistical Service)

When the pie chart is more complex than the data (Junk Charts)

How your colorblind and colorweak readers see your colors (Datawrapper)

What Graphs Reveal (If You Give Them Time) (Math with Bad Drawings)

Slow Reveal Graphs

Survival Analysis in Alteryx and Tableau; or, the survival of biscuits (Gwilym Lockwood)

Meta data

Viral content: Appy talk, keep talkin' appy talk, talk about things you'd like to do

Next phase of NHS coronavirus (COVID-19) app announced (DHSC)

UK virus-tracing app switches to Apple-Google model (BBC News)

Turn it off and on again: lessons learned from the NHS contact tracing app (Ada Lovelace Institute)

Personal data and coronavirus (IfG)

Trinity study confirms accuracy concerns on contact tracing apps (Trinity College Dublin)

What happened to Matt Hancock's coronavirus contact-tracing app? (The Bureau of Investigative Journalism)

Coronavirus: Contact-tracing apps face further hitches (BBC News)

Looking at the recently-released SAGE documents on contact tracing, it's striking how central the app is to the whole plan (Rowland Manthorpe)

You may be wondering what's going on with the contact tracing app... (Rowland Manthorpe)

Bahrain, Kuwait and Norway contact tracing apps among most dangerous for privacy (Amnesty International)

Viral content: oh, the immunity

Plans for coronavirus immunity passports should worry us all (Wired)

Explainer: Immunity certificates (CDEI)

Centre for Data Ethics and Innovation criticised after supporting controversial immunity passports (NS Tech)

Viral content: everything else

Just How Historic Is the Latest Covid-19 Science Meltdown?* (Wired)

Landmark IT deal will provide access to digital tools and save hundreds of millions of pounds for the NHS (NHS Digital)

How Data Became One of the Most Powerful Tools to Fight an Epidemic* (New York Times)

Out of the shadows: The value of data in times of crisis (Ed Humpherson for ADR UK)

Public Health in the Information Age: Recognising the Infosphere as a Social Determinant of Health (Jessica Morley, Josh Cowls, Mariarosaria Taddeo, Luciano Floridi)

The Economy Is Reeling. The Tech Giants Spy Opportunity.* (New York Times)

Data and Covid-19: why standards matter (ODI)

Data in the time of Covid-19 (Understanding Patient Data)

A rapid online deliberation on COVID-19 technologies: building public confidence and trust (Ada Lovelace Institute)

A prototype that compares coronavirus response sites (Public Digital, via Andrew)

AI Barometer (CDEI)

Alternative visions for the future of AI (Nesta)

Everyone’s talking about ethics in AI. Here’s what they’re missing (Fast Company)

Joint Statement from founding members of the Global Partnership on Artificial Intelligence (DCMS/Office for AI)

Geospatial awareness

Unlocking the power of location:The UK’s geospatial strategy (Geospatial Commission)

Reviews: Owen, Jeni, Peter, Anna

Geospatial Commission Charter (Geospatial Commission)

Geospatial Glossary (Geospatial Commission)

Parliament

Developer hub (UK Parliament)

Report on Digital Development (Stance for Parliamentary Digital Service, October 2019)

Government

Seeing government, being seen by government. (Alex)

The role of technology in governance: The example of Privacy Enhancing Technologies (Natasha McCarthy and Franck Fourniol for Data & Policy)

NI civil servant voices warning on deleted emails (BBC News)

A question for government data people (James Plunkett)

What we learnt from the first phase of the GovTech Catalyst (GDS)

Everything else

Police in England and Wales dropping rape inquiries when victims refuse to hand in phones (The Guardian)

Mobile phone data extraction by police forces in England and Wales: Investigation report (ICO)

The Mainstream Media Won’t Tell You This* (The Atlantic)

IBM, Microsoft, and Amazon’s face recognition bans don’t go far enough (Fast Company)

TALES FROM THE CRYPTO (Frank Pasquale for Public Books)

Facebook to let users turn off political adverts (BBC News)

The three tests of internet regulation (Heather Burns)

Opportunities

EVENT: Why GovCamp North? (GovCamp North)

EVENT: Shoshana Zuboff meets Margrethe Vestager: A conversation about a future digital Europe - webinar (Danish Society of Engineers)

JOB: Deputy Head, Office for Artificial Intelligence (DCMS/BEIS)

JOB: Economic Advisor - Lead Analyst - Office of Artificial Intelligence (DCMS/BEIS)

JOB: Director of Privacy Enhancing Technologies (NHS Digital)

JOB: Head of Software Development (DfE)

And finally...

Maps

Country names in any language (Arun Ganesh)

Here's the geographical distribution of the 10 most common pub names in Great Britain (Colin Angus)

The topologist's map of the world - a map showing international borders, and nothing else (r/MapPorn)

Everything else

HTTP status codes as emoji .. this might be a good idea? (@francesc)

Chart shows the changing appearance of copper throughout the patina process (via Simon Kuestenmacher)

#registers (via Max Fras, via Oliver)

Won't somebody please...

0 notes

warninggraphiccontent · 6 years ago

Text

8 November 2019

Ministry of sound

What do civil service staff numbers sound like? How about government defeats in the House of Commons?

Yes, as heavily trailed last week, I ventured into data sonification for the new IfG podcast, Inside Briefing, setting our charts on the change in civil service staff numbers since 2010 and on Commons defeats by prime ministers since 1945 to music. There seems to be a lot of interest in sonification as a way of bringing data to life - if you know of any relevant links, please send them my way (and I'm looking forward to seeing what The Economist are going to press play on sometime soon).

The sonifications (do we need a better phrase? Sound chart? Son-chart-a? Con-chart-o?) got this week's Data Bites off to a rousing, musical start. Four more fantastic presentations - from Miranda at Ordnance Survey, Nic at the Oil & Gas Authority, David at 360Giving and Miranda at the ODI - that are well worth your time. Pencil 4 December into your diary - if we don't have an event (we're still looking for funding, the pre-election period makes it difficult to get civil servants on stage), we'll probably go for a drink or two instead.

It was a joy, as ever, to make Open Data Camp (#odcamp) this Sunday - a huge thank you to Giuseppe, Angharad and all the campmakers for their hard work, the fruits of which are recorded here. Ian roped me into helping with a session on data visualisation, which did indeed take in musical data, spaceships and Star Wars (and I stand by my claim that Episode III: Revenge of the Sith is a great example of terrible dataviz ). A strong thought, prompted by excellent sessions from Mor (on 'data literacy for whom?'), Tim and Simon: as a community, we have a memory problem - lots of good stuff has been achieved and there are great resources out there but too often we're not making the most of them, we're not making them as easy to find/sharing learning as well as we could and (as Miranda M also touched on at Data Bites) we're still quoting CityMapper as the alpha and omega of open data impact.

I also enjoyed the first Office for Statistics Regulation conference - follow their new Twitter account here. And some more changing of the civil society data guard - congratulations to Hetan on moving from the Royal Statistical Society to become the new chief exec of the British Academy!

Finally, I'll be speaking at the #ODISummit on Tuesday - hopefully see some of you there!

Have a great weekend

Gavin

Today's links:

Graphic content

#GE2019

MPs standing down - here, here, here and here (Ketaki and me for IfG - more to come...)

Spreadsheet (IfG)

Standing down and length of service (Andrew Gray)

State of the parties, defeats, ministerial resignations, December elections and much more (IfG)

2017 vs 2019 (Matt Chorley)

The largest voter movements are... (Chris Curtis)

A British election and other uncertainties* (The Economist)

UK general election: Can Boris Johnson break Labour’s ‘red wall’?* (FT)

Step-by-step scatter (FT)

Brexit has lowered the bar for election victory, study finds* (FT)

The 2019 general election battleground constituencies* (FT)

Three anti-Brexit parties launch election pact in 60 seats* (FT)

The potential power of non-voters to change the face of UK politics overnight, in three maps. (David Ottewell)

Signal and noise

Inside Briefing (IfG)

SONIFICATION: Civil service staff numbers (me for IfG)

SONIFICATION: Government defeats in the House of Commons (me for IfG)

US politics

Live election results* (New York Times)

Election results* (Washington Post)

Doug Jones Thinks He’s Supposed To Be Here (FiveThirtyEight)

What’s next in the Trump impeachment inquiry, and will Trump cooperate with it?* (Washington Post)

Maps

#30DayMapChallenge

All of New York's roads, arranged by length (Dylan Moriarty)

India’s toxic smog is a common affliction in middle-income countries* (The Economist)

A demolition of the traditional county election map (Alberto Cairo via Simon Rogers)

Victorian London’s Wealth and Poverty, Mapped Block by Block (CityLab)

‘GOD’S ACRES’: THE LAND OWNED BY THE CHURCH COMMISSIONERS (Who Owns England?)

How Would Elizabeth Warren Pay for Her Sweeping Policy Plans?* (New York Times, via Marcus)

London Underground: the dirtiest place in the city* (FT)

Constituency by deprivation charts: England, whole UK, GIF, more (Alasdair Rae)

And more (Carl Baker)

The shape of things to come: Charting the changing size and shape of the UK state (Resolution Foundation)

Help to Buy Equity Loan scheme Data Visualisation (NAO, via Benoit)

Parties’ spending plans signal the return of ‘1970s-sized state’* (FT)

Everything else

Lewis Hamilton's sixth F1 world title: the stats (BBC Sport)

Greta Thunberg accuses rich countries of “creative carbon accounting”* (The Economist)

Power play: How Chinese money damned Myanmar’s economic transition (Frontier Myanmar)

Who are the NextGen? A portrait in data* (FT)

Visualizing KEXP: 18 years of playlist data that shaped Seattle music history (Tableau)

A year in Graphic detail (Alex Selby-Boothroyd)

Meta data

Politics

Big Tech has moved from offering utopia to selling dystopia* (FT)

Letter to leaders of major political parties in advance of the December 2019 general election (UK Statistics Authority)

Statements about public funding: what to look out for (Office for Statistics Regulation)

We need laws for the digital age to keep elections fair* (Amber Rudd in The Times)

Why Twitter’s ban on political ads isn't as good as it sounds (The Guardian)

How memes got weaponized: A short history (MIT Technology Review)

Future tech

Tech Buzzwords (via Lewis)

Cyber Security Incentives & Regulation Review: Call for Evidence (DCMS)

It’s seriously strange how we choose to dehumanize data but anthropomorphize AI systems (Deb Raji)

Uber’s Self-Driving Car Didn’t Know Pedestrians Could Jaywalk* (Wired, via Marcus)

Everything else

Digital Public Assets: Rethinking value, access and control of public sector data in the platform age (Common Wealth)

Transforming GOV.UK: the future of digital public services (Government Digital Service)

National Data Strategy 2030 Vision: the public conversation begins (DCMS)

Dough! Jobs microsite for UK's data watchdog set hundreds of cookies without visitors' consent (The Register)

When open government becomes a matter of life and death* (Apolitical)

The British Academy appoints new Chief Executive Hetan Shah (The British Academy)

Events and opportunities

Data Bites #7 (Institute for Government)

#IFGDataBites

#odcamp

Open Data Camp

EVENT: W.E.B. Du Bois: Charting Black Lives (House of Illustration)

PUBLIC APPOINTMENTS: Non-Executive Directors, UK Statistics Authority

JOBS: including Head of Data Science Capability (ONS Data Science Campus)

And finally...

Politics

Lib Dem bar charts (Ridge on Sunday)

Westminster voting intentions, stitched (Heidi)

"it looks like you're overstating a difference that's within margin of error" (Ariel Edwards-Levy - topical...)

Everything else

The other race that stops the nation: watch contenders jostle for a top 10 spot in bird of the year (The Guardian)

“Data is the new oil” - the origin (via @imperica)

Hoovering up your data (Carl Miller)

Forbidden love: the changing attitudes to office romance* (FT)

Thanksgiving (YouGov)

Help, our train home is making 9 quintillion stops. (Neil Codling)

Wow you know I was really worried about WeWork's future, but... (@zebulgar, via Alice)

Pie chart of the week (via everybody - given the percentages add up to 360, I think someone may have got percentages and degrees confused...)

0 notes

warninggraphiccontent · 6 years ago

Text

19 April 2019

Trust issues

How we access, share and use data in a way that balances utility and privacy is one of the defining questions of our time (#LifeBeyondBrexit). This week, the ODI published a new report on Data Trusts, one approach to more trustworthy data stewardship. (More links in the Meta data section below.)

At first glance, it looks like a comprehensive introduction to the subject and key questions - I'm looking forward to reading it in more detail (this is the sort of penetrating, scintillating insight you signed up to this newsletter for, isn't it?).

In the meantime, some further related reading: here's the ODI's polling on attitudes to data sharing from 2018, me on the Royal Statistical Society's 2014 polling on the same subject, and Onora O'Neill's 2002 Reith Lectures on trust and trustworthiness.

Naturally, having wondered where all the sport visualisation was last week while trying to chart the Six Nations, a few things popped into my timeline this week, not least this from The Upshot on the 1,000th F1 grand prix. Chris had a few suggestions for further rugby-related viz - other ideas very welcome.

Finally, you can now book your place at our second IfG Data Bites event, taking place on Wednesday 1 May. A reminder of how much fun the first one was here. And you might want to put Tuesday 4 June in your diary for the third one.

Happy Easter!

Today's links:

Graphic content

Electoral dysfunction

EU Parliament voting intention (10-11 April) (YouGov)

Critique, and class (pt 2), gender, geography (Ian Warren)

How to visualize elections using Flourish (Flourish)

Disunity to cost anti-Brexit parties seats in Europe poll* (FT, via Lee)

Party branding and colours - John Burn-Murdoch, Lisa Charlotte Rost (viaLee)

EU election results (Johnny for IfG)

Photo Finnish

Visualizing Finnish elections (Topi Tjukanov)

Finland, election result (Europe Elects, via Aron)

Maps

Visualizing 200 Years of U.S. Population Density (Visual Capitalist, viaMaddy)

Suffering from Brexhaustion? Have some more maps (Alasdair Rae)

Maps of NHS waiting times across England (Rob Findlay, via Graham)

These maps show how hard it is to measure inequality in English council areas (CityMetric)

Why Budapest, Warsaw, and Lithuania split themselves in two (The Pudding)

IfG

How the Government should approach negotiations on the UK’s long-term future relationship with the EU (Institute for Government)

Ministerial resignations, again (Alasdair for IfG)

Canada shows the way on government financial transparency (Martin for IfG)

Everything else

American inequality reflects gross incomes as much as taxes* (The Economist)

Half of England is owned by less than 1% of the population (The Guardian)

Crunched: the numbers behind big tech's tax avoidance* (FT)

For a visual on how much was redacted, here is an image with all the page thumbnails. (Amadis Kay, via Tess)

What First-Quarter Fundraising Can Tell Us About 2020 (FiveThirtyEight)

The Chinese Grand Prix in 60 seconds* (The Upshot)

Age x minutes (@Worville)

Behind the viz

The Design Process of “Why Do Cats & Dogs ...?” (Nadieh Bremer)

At @puddingviz we just published our team story idea backlog (Russell Goldenberg, via Alice)

Tableau Best Practises Put to the Test (Natalie Leach, Wellcome)

Meta data

Data trusts

Data trusts: lessons from three pilots (report) (ODI)

Huge appetite for data trusts, according to new ODI research (ODI)

Putting the trust in data trusts (Register Dynamics)

Commentary from the launch (Simon Burall)

Why we need a better term (Mor Rubinstein)

Opportunities

EVENT: Data Bites #2: Getting things done with data in government (Institute for Government - watch the first one here)

JOBS: Strategy & Governance Advisor; Policy Advisor - Analyse & Anticipate (Centre for Data Ethics and Innovation)

Openness

United Kingdom End-of-Term Report 2016-2018 – For Public Comment(via Ben Worthy)

BETTER DATA FOR FAIRER EMPLOYMENT: STATISTICS’ ROLE IN TACKLING THE GENDER PAY GAP (Royal Statistical Society)

A short interview with Significance Magazine on the motivation for OurWorldInData (Max Roser)

The Perils of Public Engagement (Doteveryone, via Tess)

An open data leader in government: “It doesn’t have to be perfect to be useful”* (Apolitical)

Location, location, location

Mapping the world in 3D will let us paint streets with augmented reality*(MIT Technology Review)

What big data uncovers about how people use their city centres (Centre for Cities)

Facebook's AI team maps the whole population of Africa (TechCrunch)

Everything else

15 MONTHS OF FRESH HELL INSIDE FACEBOOK* (Wired)

Data Delivery Group (Scottish Government)

A Chief Digital and Data Officer with actual powers (via Jeni Tennison)

Home Office plans Crime Prevention Data Lab (UKAuthority)

Diversity Alone Will Not Be The Solution To Bias In AI (Dawn Duhaney for POCIT)

eBay for government? Ukraine’s online store has sales in the billions*(Apolitical)

The white paper on online harms is a global first. It has never been more needed (The Guardian)

One Month, 500,000 Face Scans: How China Is Using A.I. to Profile a Minority* (New York Times)

And finally...

Wild, wild Westeros

Jon Snow is fan favourite to win Game of Thrones (YouGov)

How Game of Thrones changed television* (FT)

Who will ‘win’ Game of Thrones? Play our interactive game and make your season 8 predictions* (Telegraph)

An illustrated guide to all 2,339 deaths in ‘Game of Thrones’* (Washington Post)

The good

A map showing the most common local politicians' names in different places (David Ottewell, via Lucy and Nick - more here)

the population of the UK – joy division style (Niko Kommenda)

#JUVAJA (@JurgenJee)

When you're marrying the human you met while collaborating on#dataviz together, you're basically required to collaborate on some viz for the wedding, right? (Amy Cesal, via Tess)

Where Would You Draw the Line?* (New York Times)

GDPR is my therapist (Vinay Patel)

The bad

Government in email privacy blunder (BBC News)

Square pie charts (via Ben Stanley)

Easily the funniest data viz I've ever seen (Dorsa Amir, via Daniel)

The egg-ly

Eggflation (Garry White, via Tim)

0 notes