Creative Lab Report: Data | Culture | Learning

[Summary: report from a one day workshop with Create Gloucestershire bringing together artists and technologists to create artworks responding to data. Part 2 in a series with Exploring Arts Engagement with (Open) Data]

What happens when you bring together a group of artists, scientists, teachers and creative producers, with a collection of datasets, and a sprinkling of technologists and data analysts for a day? What will they create? What can we learn about data through the process?  

There has been a long trend of data-driven artworks, or individual artists incorporating responses to structured data in their work. But how does this work in the compressed context of a one-day collaborative workshop? These are all questions I had the opportunity to explore last Saturday in a workshop co-facilitated with Jay Haigh of Create Gloucestershire and hosted at Atelier in Stroud:  an event we ran under the title “Data | Create | Learning: Creative Lab”

The steady decline in education spending and increased focus on STEM subjects has impacted significantly on arts teaching and teachers. The knock on effect is observed in the take up of arts subjects at secondary, further and higher education level and, ultimately, impacting negatively on the arts and cultural sector in the UK. As such, Create Gloucestershire has been piloting new work in Gloucestershire schools to embed new creative curriculum approaches, supporting its mission to ‘make arts everyday for everyone’. The cultural education agenda therefore provided a useful ‘hook’ for this data exploration. 

Data: preparation

We started thinking about the idea of a ‘art and data hackathon’ at the start of this year, as part of Create Gloucestershire’s data maturity journey and decided to focus on questions around cultural education in Gloucestershire. However, we quickly realised an event could not be entirely modelled on a classic coding hackathon event, so, in April we brought together a group of potential participants for a short design meeting. 

Photo of preparation workshop

For this, we sought out a range of datasets about schools, arts education, arts teaching and funding for arts activities – and I worked to prepare Gloucestershire extracts of these datasets (slimming them down from hundreds of columns and rows) . Inspired by the Dataset Nutrition Project project, and using AirTable blocks to rapidly create a set of cards, we took along profiles of some of these datasets to help give participants at the planning meeting a sense of what might be found inside each of the datasets we looked at. 

Dataset labels: inspired by dataset nutrition project
Through this planning meeting we were able to set our expectations about the kind of analysis and insights we might get to from these datasets, and to think about placing the emphasis of the day on collaboration and learning, rather than being overly directive about the questions to be answered with data. We also decided that, in order to help collaborative groups form in the workshop, and to make sure we had materials prepared for particular art forms, we would invite a number of artists to act as anchor facilitators on the day.

Culture: the hackathon day 

Group photo of hackathon day

After an overview of Create Gloucestershire’s mission to bring about ‘arts everyday for everyone’, we began with introductions, going round the group and completing three sentences:

  • For me, data is…
  • For me, arts everyday is…
  • In Gloucestershire, is arts everyday….? 

For me, data is... (post-it notes)

Through this, we began to surface different experiences of engagement with data (everywhere; semi-transparent; impersonal; information; a goldmine; less well defined than art; complex; connective…), and with questions of access to arts (Arts everyday is: fun; making sense of the world; what you make of it; necessary; a privilege for some; an improbable dream; essential). 

We then turned briefly to look at some of the data available to explore these questions, before inviting our artists to explain the tools and approaches they had brought along to share:

  • Barney Heywood of Stand + Stare demonstrated use of touch-sensitive tape to create physical installations that respond to an audience with sound or visuals, as well as the Mayfly app that links stickers and sounds;
  • Illustrator and filmmaker, Joe Magee described the power of the pen, and how to sketch out responses to data;
  • Digital communications consultant and artist, Sarah Dixon described the use of textiles and paper to create work that mixes 2D and 3D; and
  • Architect Tomas Millar introduced a range of Virtual Reality technologies, and how tools from architecture and gaming could be adapted to create data-related artworks. 

To get our creative ideas flowing, we then ran through some rapid idea generation, with everyone rotating around our four artists groups, and responding to four different items of data (below) with as many different ideas as possible. From the 30+ ideas generated came some of the seeds of the works we then developed during the afternoon.

Slides showing: 38% drop in arts GCSE entries 2010 to 2019; Table of number and percentage of students a local secondary schools eligible for free school meals; Quantitative and qualitative data from a study on arts education in schools.

Following a short break, everyone had the chance to form groups and dig deeper into designing an artwork, guided by a number of questions:

  • What response to data do group members want to focus on? Collecting data? Data representation? Interpretation and response? Or exploring ‘missing data’?
  • Is there a story, or a question you want to explore?
  • Who is the audience for your creation?
  • What data do you need? Individual numbers; graphs; tables; geo data; qualitative data; network data or some other form? 
Example of sketches
Sketching early ideas

Groups then had around three hours to start making and creating prototype artworks based on their ideas, before we reconvened for a showcase of the creations.

The process was chaotic and collaborative. Some groups were straight into making: testing out the physical properties of materials, and then retrofitting data into their works later. Others sought to explore available datasets and find the stories amongst a wall of statistics. In some cases, we found ourselves gathering new data (e.g. lists of extracurricular activities taken from school websites), and in others, we needed to use exploratory data visualisation tools to see trends and extrapolate stories that could be explored through our artforms. People moved between groups to help create: recording audio, providing drawings, or sharing skills to stimulate new ways of increasing access to the stories within the data. Below is a brief summary of some of the works created, followed by some reflections on learning from the day. 

The artworks

Interactive audio: school subjects in harmony

Artwork: Barney Heywood and team | Photo credit: Kazz Hollick

Responding to questions about the balance of the school curriculum, and the low share of teaching hours occupied by the arts, the group recorded a four-part harmony audio clip, and set the volume of each part relative to the share of teaching time for arts, english, sciences and humanities. Through a collection of objects representing each subject, audiences could trigger individual parts, all four parts together, or a distorted version of the harmony. Through inviting interaction, and using volume and distortion, the piece invited reflection on the ‘right’ balance of school subjects, and the effect of loosing arts from the curriculum for the overall harmony of education. 

Fabric chromatography: creative combinations

Artwork: Sarah Dixon and team. Photo credit: Jay Haigh

 Picking up on a similar theme, this fabric based project sought to explore the mix of extracurricular activities available at a school, and how access to a range of activities can interact to support creative education. Using strips of fabric, woven in a grid onto a backcloth, the work immersed a dangling end of each strip in coloured ink, the mix of inks depending on the range of arts activities available at a particular school. As the ink soaked up vertical strands of the fabric, it also started to seep into horizontal strands, which could mix with other colours. The colours chosen reflected a chart representation of the dataset used to inform the work, establishing a clear link between data, information, and art work.

This work offered a powerful connection between art, data and science: allowing an exploration of how the properties of different inks, and different fabrics, could be used to represent data on ‘absorption’ of cultural education, and the benefits that may emerge from combining different cultural activities. The group envisaged works like this being developed with students, and then shown in the reception area of a school to showcase it’s cultural offer. 

The shrinking design teacher (VR installation)

Artwork: Tomas Millar & Pip Heywood. Photo credit: Jay Haigh

Using a series of photographs taken on a mobile phone, a 3D model of representation of Pip, a design teacher, was created in a virtual landscape. An audio recording of Pip describing the critical skill sets engendered through design teaching was linked to the model, which was set to shrink in size over the time of the recording reflecting 7-years of data on the reduction in design teaching hours in school.

Observed through VR goggles, the piece offered an emotive way to engage with a narrative on the power of art to encourage critical questioning of structures, and to support creative engagement with the world, all whilst – imperceptibly at first, and more clearly as the VR observer finds themselves looking down at the shrinking teacher – highlighting current trends in teaching hours. 

Arcade mechanicals

Artwork: Joe Magee and team. Photo credit: Jay Haigh

From the virtual to the physical, this sketch questioned the ‘rigged’ nature of grammar school and private education, imagining an arcade machine where the weight, size and shape of tokens were set according to various data points, and where the mechanism would lead to certain tokens having a better chance of winning. 

By exploring a data-informed arcade mechanisms, this idea captures the idea that statistical models can tell us something about potential future outcomes, but that outcomes are not entirely determined, and there are still elements of chance, or unpredictable interactions, in any individual story. 

Exclusion tags

Artwork: Joe Magee, Sarah Dixon and team. Photo: Jay Haigh

Building on data about different reasons for school exclusion, eight workshop participants were handed paper tags, marking them out for exclusion from the ‘classroom’. They were told to leave the room, where the images on their tags were scanned (using the Mayfly app) playing them a cold explanation of why they have been excluded and for how long.

The group were then invited to create a fabric based sculpture to represent the percentage of children excluded from school in Gloucestershire for the reasons indicated on their tag.  

The work sought to explore the subjective experience of being excluded, and to look behind the numbers to the individual stories – whilst also prototyping a possible creative yarn-bombing workshop that could be used with excluded young people to re-engage them with education.  

The team envisaged a further set of tags linked to personal narratives collected from young people excluded from school, bringing their voices into the piece to humanise the data story.

Library lights: stories from library users

This early prototype explored the potential VR to let an audience explore a space, shedding light on areas that are otherwise in darkness. Drawing on statistics about the fact that 33% of people use libraries, and on audio recordings – drawn from direct participant quotes collected by Create Gloucestershire during their 3-year Art of Libraries test programme describing how people benefitted from engagement with arts interventions in libraries across Gloucestershire – a virtual space was populated with 100 orbs – the percentage lit relating to those who use libraries. As the audience in VR approached a lit orb, an audio recording of an individual experience with a library would play. 

The creative team envisaged the potential to create a galaxy of voices: offseting negative comments about libraries from those that don’t use them (they were able to find a significant number of data sets showing negative perceptions about libraries, but few positive ones) with the good experiences of those that do.

Artwork: Tomas Millar and team (image to come)

Seeing our networks


Not so much an artwork, as a data visualisation, this piece took data gathered over the last five years by Create Gloucestershire to record attendance at Create Gloucestershire events. Adding in data on attendance at the Creative Lab, lists of people, events and event participation (captured and cleaned up using the vTiger CRM), were fed into Kumu, and used to build an interactive network diagram. The visual allows an identification of how, over time, CG events have both engaged with new people (out on the edge of the network), and have started to build ongoing connections. 

A note on naming

*One things we forgot to do (!) in our process was to ask each group to title their works, so the titles and descriptions above are given by the authors of this post. We will happily amend with input from each group. 

Learning

We closed our workshop reflecting on learning from the day. I was particularly struck by the way in which responding to dataset through the lens of artistic creation (and not just data visualisation) provided opportunities to ask new questions of datasets, and to critically question their veracity and politics: digging into the stories behind each data point, and powerfully combining qualitative and quantitative data to look not just at presenting data, but finding what it might mean for particular audiences. 

However, as Joe Magee framed it, it wasn’t always easy to find a route up the “gigantic data coalface”. Faced with hundreds of rows and columns of data, it was important to have access to tools and skills to carry out quick visualisations: yet knowing the right tools to use, or how to shape data so that it can be easily visualised, is not always straightforwards. Unlike a classic data hackathon, where there are often demands for the ‘raw data’, a data and art creative lab benefits from more work to prepare data extracts, and to provide access to layers of data (individual data points, a small set they belong in, the larger set they come from) . 

Our journey, however, took use beyond the datasets we had pre-prepared. One particular resource we came across was the UK Taking Part Survey which offers a range of analysis tools to drill down into statistics on participation in art forms by age, region and socio-economic status. With this dataset, and a number of others, our expectations were often confounded when, for example,  relationships we had expected to find between poverty and arts participation, or age and involvement, were not borne out in the data. 

This points to a useful symmetry: turning to data allowed us to challenge the assumptions that might otherwise be baked into an agenda-driven artwork, but engaging with data through an arts lens also allowed us to challenge the  assumptions behind data points, and behind the ways data is used in policy-making. 

We’ve also learnt more about how to frame an event like this. We struggled to describe it in advance and to advertise it. Too much text was the feedback from some! Now with images of this event, we can think about ways to provide a better visual story for future workshops of what might be involved. 

Given Create Gloucestershire’s commitment to arts everyday for everyone as a wholly inclusive statement of intent, it was exciting to see collaborators on the day truly engaging with data in a way they may not have done previously, and then expanding access to it by representing data in accessible and engaging forms which, additionally, could be explored by subjects of the data themselves.  What might have seemed “boring” or “troublesome” at the start of the day become a font of inspiration and creativity, opening up new conversations that may never have previously taken place and setting up the potential for new collaborations, conversations, advocacy and engagement.

Thanks

Thank you to the team at Create Gloucestershire for hosting the day, and particularly to Caroline, Pippa and Jay for all the organisation. Thanks to Kat at Atelier for hosting us, and to our facilitating artists: Barney, Sarah, Thomas and Joe. And thanks to everyone who gave up a Saturday to take part!

Photo credit where not stated: Jay Haigh

Exploring Arts Engagement with (Open) Data

[Summary: Over the next few months I’m working with Create Gloucestershire with a brief to catalyse a range of organisational data projects. Amongst these will be a hackathon of sorts, exploring how artists and analysts might collaborate to look at the cultural education sector locally. The body of this post shares some exploratory groundwork. This is a variation cross-posted from the Create Gloucestershire website.]

Update: For part 2 – about the event we held, see Creative Lab Report: Data | Culture | Learning.

Pre-amble…

Create Gloucestershire have been exploring data for a while now, looking to understand what the ever-increasing volume of online forms, data systems and spreadsheets arts organisations encounter every day might mean for the local cultural sector. For my part, I’ve long worked with data-rich projects, focussing on topics from workers co-operatives and youth participation, to international aid and corruption in government contracting, but the cultural sector is a space I’ve not widely explored.

Often, the process of exploring data can feel like a journey into the technical: where data stands in opposition to all things creative. So, as I join CG for the next three months as a ‘digital catalyst’, working on the use of data within the organisation, I wanted to start by stepping back, and exploring the different places at which data, art and creativity meet with an exploratory blog post..

…and a local note on getting involved…

In a few weeks (late February 2019) we’ll be exploring these issues through a short early-evening workshop in Stroud: with a view to hosting a day-long data-&-art hackathon in late Spring. If you would like to find out more, drop me a line.

Post: Art meets data | Data meets art

For some, data and art are diametrically opposed. Data is about facts. Art about feelings.

Take a look at writings from the data visualisation community [1], and you will see some suggest that data art is just bad visualisation. Data visualisation, the argument runs, uses graphical presentation to communicate information concisely and clearly. Data art, by contrast, places beauty before functionality. Aesthetics before information.

Found on Flickr: “I’m not even sure what this chart says … but I think its gorgeous!” (Image CC-BY Carla Gates / Original image source: ZSL)

I prefer to see data, visualisation and art all as components of communication. Communication as the process of sharing information, knowledge and wisdom.

The DIKW pyramid proposes a relationship between Data, Information, Knowledge and Wisdom, in which information involves the representation of data into ‘knowing that’, whilst knowledge requires experience to ‘know how’, and wisdom requires perspective and trained judgement in order to ‘know why’. (Image CC BY-SA. Wikimedia Commons)

Turning data into information requires a process of organisation and contextualisation. For example, a collection of isolated facts may be made more informative when arranged into a table. That table may be made more easily intelligible when summarised through counts and averages. And it may communicate more clearly when visualisation is included.

An Information -> Data -> Information journey. GCSE Results in Arts Subjects. (Screenshots & own analysis)

But when seeking to communicate a message from the data, there is another contextualisation that matters: contextualising to the recipient: to what they already know, or what you may want to them to come to know. Here, the right tools may not only be those of analysis and visualisation, but also those of art: communicating a message shaped by the data, though not entirely composed of it.

Artistic expression could focus on a finding, or a claim from the data, or may seek to support a particular audience to explore, interrogate and draw interpretations from a dataset. (Image CC BY-SA Toby Oxborrow)

In our upcoming workshop, we’ll be taking a number of datasets about the state of cultural education in Gloucestershire, and asking what they tell us. We’ll be thinking about the different ways to make sense of the data, and the ways to communicate messages from it. My hope is that we will find different ways to express the same data, looking at the same topic from a range of different angles, and bringing in other data sources of our own. In that way, we’ll be able to learn together both about practical skills for working with data, and to explore the subjects the data represents.

In preparing for this workshop I’ve been looking at ways different practitioners have connected data and art, through a range of media, over recent years.

The Open Data Institute: Data as Culture

Since it’s inception, The Open Data Institute in London has run a programme called ‘Data as culture’, commissioning artists to respond to the increasing datification of society.

Some works take a relatively direct approach to representation, selecting particular streams of data from the web and using different media to represent them. Text trends, for example, selected and counterposes different google search trends on a simple graph over time. And the ODIs infamous vending machine provides free crisps in response to news media mentions of recession.

Text Trends. From ODI Website and Data Soliloquies book.

In representative works, the artist has chosen the signal to focus on, and the context in which it is presented. However, the underlying data remains more or less legible, and depending on the contextual media and the literacies of the ‘reader’, certain factual information can also be extracted from the artwork. Whilst it might be more time-consuming to read, the effort demanded by both the act of creation, and the act of reading, may invite a deeper engagement with the phenomena described by the data. London EC2 explores this idea of changing the message through changing the media: by woodblock printing twitter messages, thus slowing down the pace of social media, encouraging the viewer to rethink otherwise ephemeral information.

In other works that are directly driven by datasets, data is used more to convey an impression rather than to convey specific information. In the knitted Punchcard Economy banners, a representation working hours is combined with a pre-defined message resulting in data that can be read as texture, more than it can be read as pattern. In choosing how far to ‘arrange’ the data, the work finds its place on a spectrum between visualisation or aesthetic organisation.

Punchcard Economy, Sam Meech, 2013. ODI: 3.5 x 0.5m knitted banner, FutureEverything: 5 x 3m knitted banner & knitting machines.

Other works in the data as culture collection start not from datasets, but from artists responses to wider trends of datification. Works such as metographyflipped clock and horizon respond to forms of data and it’s presentation in the modern world, raising questions about data and representation – but not necessarily about the specific data which happens to form part of the work.

Flipped Clock, Thomson & Craighead, 2008. ODI Data as Culture.

Other works still, look for the data within art, such as pixelquipu which takes it’s structure from pre-Columbian quipu (necklace-shaped, knotted threads from the Inca empire, that are thought to contain information relating to calendars and accounting in the empire). In these cases, turning information into data, and then representing it back in other way, is used to explore patterns that might not have otherwise been visible.

YoHa: Invisible Airs

Although it has also featured in the ODI’s Data as Culture collection, I want to draw out and look specifically at YoHa’s ‘Invisible Airs’ project. Not least because it was the first real work of ‘open data art’ I encountered, stumbling across it at an event in Bristol.

As newly released public spending records appear on screen, a pneumatically powered knife stabs a library book, sending a message about budget cuts, and inviting scrutiny of the data on screen.

It is a hard project to describe, but fortunately YoHa have a detailed project description and video on their website, showing the contraptions (participatory kinetic sculptures?) they created in 2014, driven by pneumatic tubes and actuated by information from Bristol City Council’s database of public spending.


In the video, Graham Harwood describes how their different creations (from a bike seat that rises up in response to spending transactions, to a pneumatic knife stabbing a book to highlight library service cuts) seek to ‘de-normalise’ data, not in the database designers sense of finding a suitable level of data abstraction, but in the sense of engaging the participant to understand otherwise dry data in new ways. The learning from the project is also instructive: in terms of exploring how far the works kept the attention of those engaging with them, or how far they were able to communicate only a conceptual point, before viewers attention fell away, and messages from the underlying data were lost.

Ultimately though, Invisible Airs (and other YoHa works engaging with the theme of data) are not so much communicating data, as communicating again about the role, and power, of data in our society. Their work seeks to bring databases, rather than the individual data items they contain, into view. As project commissioner Prof Jon Dovey puts it, “If you are interested in the way that power works, if you are interested in the way that local government works, if you are interested in the way that corporations work, if you are interested in the way that the state works, then data is at the heart of it…. The way your council tax gets calculated… the way your education budget gets calculated, all these things function through databases.”

Everyday data arts

Data as art need not involve costly commissions. For example, the media recently picked up on the story of a german commuter who had knitted a ‘train-delay scarf’, with choice of wool and colour representing length of delays. The act of creating was both a means to record, and to communicate, and in the process communicate much more effectively than the same data might have done if simply recorded in a spreadsheet, or even placed onto a chart with data visualisation.

‘Train Delay Scarf’ – a twitter sensation in January 2019.

Data sculpture and data-driven music

In a 2011 TED Talk, Nathalie Miebach has explored both how weather data can be turned into a work of art through sculpture and music, as well as questioning how the setting in which the resulting work is show affects how it is perceived.

She describes the creation of a vocabulary for turning the data into a creative work, but also the choice of a media that is not entirely controlled by the data, such that the resulting work is not entirely determined by the data, but also by its interaction with other environmental factors.

Dance your PhD, and dancing data

When reflecting on data and art, I was reminded of the annual Dance your PhD competition. Although the focus is more on expressing algorithms and research findings, than underlying datasets, it offers a useful way to reflect on ways to explain data, not only express what it contains.

In a similar vein, AlgoRythmics explain sorting algorithms using folk dance – a playful way of explaining what’s going on inside the machine when processing data.

There is an interesting distinction though between these two. Whilst Dance your PhD entries generally ‘annotate’ the dance with text to explain the phenomena that the dance engages with audience with, in AlgoRythmics, the dance itself is the entirety of the explanation.

Visualisation

The fields of InfoViz and DataViz have exploded over the last decade. Blog such as InformationIsBeautiful, Flowing Data and Visualising Data provide a regular dose of new maps, charts and novel presentation of data. However, InfoViz and DataViz are not simply synonyms: they represent work that starts from different points of a Data/Information/Knowledge model, and with often different goals in mind.

Take, for example, David McCandless’ work in the ‘Information in Beautiful’ book (also presented in this TED Talk). The images, although often based on data, are not a direct visualisation of the data, but an editorialised story. The data has already been analysed to identify a message before it is presented through charts, maps and diagrams.

 

By contrast, in Edward Tufte’s work on data visualisation, or even statistical graphics, the role of visualisation is to present data in order to support the analytical process and the discovery of information. Tufte talks of ‘the thinking eye’, highlighting the way in which patterns that may be invisible when data is presented numerically, can become visible and intelligible when the right visual representation is chosen. However, for Tufte, the idea of the correct approach to visualisation is important: presenting data effectively is both an art and a technical skill, informed by insights and research from art and design, but fundamentally something that can be done right, or done wrong.

Graphical Practices: Page 14 of Edward Tufte ‘The Visual Display of Quantitative Information

Other data visualisation falls somewhere between the extremes I’ve painted here. Exploratory data visualisations can seek to both support analysis, but also to tell a particular story through their selection of visualisation approach. A look at the winners of the recent 360 Giving Data Visualisation Challenge illustrates this well. Each of these visualisation draws on the same open dataset about grant making, but where ‘A drop in the bucket’ uses a playful animation to highlight the size of grants from different funders, Funding Themes extracts topics from the data and presents an interactive visualisation, inviting users to ‘drill down’ into the data and explore it in more depth. Others, like trend engine use more of a dashboard approach to present data, allowing the user to skim through and find, if not complete answers, at least refined questions that they may want to ask of the raw dataset.

Funding Trends for a ‘cluster’ of arts-related grants, drawing on 360 Giving data. Creator: Xavi Gimenez

Arts meet data | Data meet arts | Brokering introductions

Writing this post has given me a starting point to explore some data-art-dichotomies and to survey and link to a range of shared examples that might be useful for conversations in the coming weeks.

It’s also sparked some ideas for workshop methods we might be able to use to keep analytical, interpretative and communicative modes in mind when planning for a hackathon later this year. But that will have to wait for a future post…

 

Footnotes

[1]: I am overstating the argument in the blog post on art and data visualisation slightly for effect. The post, and comments in fact offer a nuanced dialogue worth exploring on the relationship of data visualisation and art, although still seeking to draw a clear disjunct relationship.