After answering the questions of architects in Mosaic, I have recently responded to an interview for the monthly periodical of the Spanish geographer association. The result of the discussion is now online: La leyenda del mapa mudo – Abril 2013
I have recently contributed to the April edition of Ethnography Matters on Ethnomining and the combination of qualitative & quantitative data. My story describes the overall process of our work with sensor data at the Louvre Museum in Paris. I particularly focus on the importance of mixed-methods when its comes to give full answers about behaviors and people usage of technology.
Here is the full text: Insights from network data analysis that yield field observations.
As the year ends, tradition calls for a review of the several initiatives I engaged in during 2012. The exercise entails looking back in time with the support social network activities and more personal logs (e.g. ical, emails) to keep track of gratifying rencontres and significant milestones at the Near Future Laboratory (see last year’s A Few Things the Laboratory did in 2011).
If this year had a mantra it would be: “sketching with data”, an approach to innovate with data I presented in various conferences and institutions from the high-tech cabarets such as Strata in San Francisco; or Red Innova in Madrid to the more cozy settings of the IAAC architecture school in Barcelona. These speaking engagements were part of a polishing phase that reports on the my evolving practice fed by the accumulated experiences on the ground. For instance, I discussed our investigation on the roles of a retail bank in the ‘smart’ city of the near future. Our client had fairly good ideas of the potentials of a real-time information platform. This is the kind of service a bank is extremely familiar with. However, they had limited knowledge on the specific information that could feed and emerge from this kind of platform. As part of our consulting work, we regularly sketched advanced dashboard for participants of the project to explore and interrogate their data with fresh perspectives. The use of the prototypes helped the client craft and tune indicators that qualify commercial activities. This experience still feeds the future bank services and products based on data.
Another gratifying outcome of the work around “sketching with data” was the release in June and November of the alpha and beta versions of Quadirgram (see Unveiling Quadrigram). The product resulted from a collaboration with my friends at Bestiario and responds to the increasing demand of clients to think (e.g. sketch) freely with data. The tool is meant to diffuse the power of information visualization within organizations and eventually reach the hands of people with knowledge and ideas of what data mean. I had the unique opportunity to influence many aspects of the product development and release process (engineering, user-experience, go to market strategy, client/investor/provider meetings) and now proudly sit in the advisory board of the company.
Other fruitful collaborations took place along the year, each of them bringing their unique set of experiences. I am particularly grateful to have joined forces with Urbanscale, Claro Partners, Interactive Things, Lift, Data Side and Pop-up Urbain. While a good share of the work stayed within confidential settings, I reserved efforts for self-started initiatives such as:
- Ville Vivante: an ‘urban demo’ that took the form of a visual animation and eight posters deployed at the Geneva central station (project led by Lift Conference, in collaboration with Interactive Things).
- Footoscope: a deciphering tool for football amateurs developed in collaboration with Philippe Gargov of Pop-up Urbain. Its interface provides a perspective on the morphology and tactics of a football team according to raw data on its passing game transformed into indicators and visualizations.
Finally, I kept some quiet moments to contribute to academia with reviews for Sensors, CHI, CSCW and Just-In-Time Sociology, teach a postgraduate course on the design of ‘data services’ and published of the paper New tools for studying visitor behaviors in museums: a case study at the Louvre co-authored with Yuji Yoshimura, UPF and MIT on a follow-up investigation of our hyper-congestion study at the Louvre.
Sports have always kept a tight relationship with data to measure performances. It has been particularly the case to improve athletes capabilities with motion analysis or objectify team sports that are easily fragmented into single events (e.g. Sabermetics). With new means of producing statistics through video and sensor technologies, other sports have started the search for objective knowledge. In the domain of football (i.e. soccer) companies such as Prozone and Opta Sports have led the innovation in data collection. In parallel, some academics have been exploring this new terrain to apply their statistics-led methodology (see A network theory analysis of football strategies). Similarly, designers have also started to transform these new measures (often in real-time) into sophisticated visualization to augment the spectator’s experience (see In-screen sports graphics).
At Near Future Laboratory, we regularly investigate the implications of the emerging presence of data particularly in the domain of the city and its services. Our work requires the joint understanding of space (e.g. a territory, its rules, cultures, history), of the networks that compose the space (both physical infrastructures and digital activities) and the human behaviors manifasted in that space. As part of our self-started initiatives, we enjoy employing these prisms to explore other intriguing domains such as football. In this ‘pet project’, we collaborated with the prospective consultant Philippe Gargov of [pop-up] urbain, connoisseur and writer on the use of statistics in football (see Passer aux stats supérieures) to augment his knowledge of football and tactics with prototyped visualizations that revealed the layout of teams through the average position of players, the key players in the passing game and the orientation each player gives to the game. We called this experiment Footoscope.
Footoscope provides a perspective on the morphology and tactics of a football team according to raw data on its passing game (e.g. passes between players, positions of the players when receiving the ball, playing time) transformed into indicators (e.g. “betweenness”) and visualizations (e.g. flows in the passing game, orientation of the propagation of the ball, layout of the team). We prototyped it with Quadrigram in order to share the tools with amateurs who want to become ‘footoscopists’ and decipher data on team they know or want to explore. We tested to tool with Philippe Gargov based on the raw statistics of the World Cup in South African accessible on the FIFA web site. Philippe did a great job in mixing his knowledge on the competition with the use of Footoscope. The results (in French) discuss, for instance, the key role of Bastian Schweinsteiger in Germany’s midfield that other players such as Stankovic or An Yong Ha failed to reproduce; or the incapacity for Switzerland to manage the distances between its lines. Read more (in French) on the Footoscope web site.
The key role of Bastian Schweinsteiger in Germany’s midfield, perfectly centered and well-connecter. More on Footoscope.
The incapacity for Switzerland to manage the distances between its lines, with its defense and strikers compacted at a short distance. This contrasts with a more balance team that takes a greater advantage of spaces such as Chile below. More on Footoscope.
Why do I blog this: Our pet projects are meant to explore new domains and ideas. Like other domains (e.g. cities, organizations) the analysis of football request the understanding of space, networks (data) and behaviors (observations). The collaboration with Philippe Gargov revealed some early insights on generating the dialogue between statistics and amateur knowledge of the terrain to produce a new apprehension of the game.
Recently the independent culture research lab ZZZINC interviewed me for the Mosaic online magazine. It was a pleasure to answer Paco González‘ questions on our practice at Near Future Laboratory and our work on urban data. The result is now online: Entrevista a Fabien Girardin (English version).
So for the last 8 months I have been working almost exclusively with my friends at the information visualization consulting company Bestiario on new tools to visualize information. Last year, based on our joint experience, we detected two increasing demands within innovative institutions. First the wish to think with liberty with data, outside of coding, scripting, wizard-based or blackbox solutions. Then, we perceived the necessity to diffuse the power of information visualization within organizations to reach the hands of people with knowledge and ideas of what data mean.
Our efforts have now culminated into Quadrigram, a Visual Programming Environment to gather, shape and share living data. By living data we mean data that are constantly changing and accumulating. They can come from social network, sensor feeds, human activity, surveys, or any kind of operation that produce digital information.
For Bestiario and its long track record in ‘haute couture’ interactive visualizations, Quadrigram offers ‘prêt-à-porter’ solutions for organizations, consultants, analysts, designers and programmers working routinely with these types of data. As with other services, data visualization plays a central role in the making sense and sharing of complex data.
I got the chance to work on multiple conceptual, engineering and strategic aspects of Quadrigram. In this post I summarize four most main areas I had the pleasure to shape in collaboration with Bestiario:
1) Redefining work with data
For us at Near Future Laboratory it made sense in helping Bestiario with our experience in prototyping solutions that become feedback loops where our clients can actually figure something out. Indeed, more and more results of our investigations became interfaces or objects with a means of input and control rather than only static reports. The design of Quadrigram lays on this very idea of ‘feedback loop’ and provides a WYSIWYG (What you see is what you get) interface. It is designed for iterative exploration and explanation. Each iterations or “sketches” is an opportunity to find new questions and provide answers with data. Data mutate, take different structure in order to unveil their multiple perspectives. We like to think that Quadrigram offers this unique ability to manipulate data as a living material that can be shaped in real time or as Mike Kuniavsky nicely describes in Smart Things: Ubiquitous Computing User Experience Design: “Information is an agile material that needs a medium”. And this not only concerns ‘data scientists’ but rather everybody with knowledge and ideas in a work that involves data.
With the diffusion of access to data (e.g. the open data movement), our investigation with data has become utterly multi-disciplinary. Nowadays, our projects embark different stakeholders with fast prototyped tools that promote the processing, recompilation, interpretation, and reinterpretation of insights. For instance, our experience shows that the multiple perspectives extracted from the use of exploratory data visualizations is crucial to quickly answer some basic questions and provoke many better ones. Moreover, the ability to quickly sketch an interactive system or dashboard is a way to develop a common language amongst varied and different stakeholders. It allows them to focus on tangible opportunities of product or service that are hidden within their data. I like to call this practice ‘Sketching with Data‘, others such as Matt Biddulph talks about “Prototyping with data” (see also Prototyping location apps with real data). Regardless of the verb used, we suggest a novel approach to work data in which analysis and visualizations are not the unique results, but rather the supporting elements of a co-creation process to extract value from data. In Quadrigram, the tools to sketch and prototype took the form of a Visual Programming Environment.
The teaser video summarize the vision behind Quadrigram
2) Reducing the barriers of data manipulation
Visual Programming Environments have flourished in the domain of information technologies, starting with LabVIEW in the 80s and then spreading to the emerging fields mixing data with creativity such as architecture, motion graphic and music. In these domains, they have demonstrated virtues in reducing the barrier of entry for non-experts (check the VL/HCC community for more on the topic). In the Visual Programming Environment we developed, users manipulate in an interactive way pre-programmed modules represented as graphical elements. When connected, these modules form a ‘data flow’ (also called dataflow programming) that provide a constant visual awareness the result of the program (“What You See Is What You Get”) ideal for quick “trial and error” explorations. This way the tool allows for the evaluation of multiple pathways towards the correct solution or desired result. It inspires solution-finding for non-technical professional by exposing the full flow of data.
The take a tour video presents the Visual Programming Environment that offers a transparent way of setting up a solution, that contrast with wizard-based environments and their “black boxes”.
3) Creating a coherent language
A major challenge when grouping tools to work with data within a common Visual Programming Environments has been to define basic building blocks of a language. Starting from scratch, we used an exploratory phase that led to the release of an experimental environment called Impure and its large sets (500) of diverse modules. This free solution generated a decent community of valorous 5000 users. We used Impure as testbed for our ideas and perform the necessary user studies to come up with a coherent basic language. We particularly focused on specific action verbs (what people can do see Verbs and design and verbs) that enclose the most common operations on data: sort, search, insert, merge, count, compare, replace, remove, filter, create, get, cluster, encode, decode, convert, accumulate, split, resize, set, execute, load, save. These actions are performed on Data Structures (e.g. create List, sort Table, replace String, cluster Network, compare Date, resize Rectangle, load Image, …) within specific domains (e.g. Math, Geography, Statistics, …). The language is complemented with a growing list of Visualizers categorized according to their objectives to reveal aspects about the data (e.g. compare, contextualize, relate, …). Through this structure (actions – structure – domain) user can find the appropriate module within a very dense and diverse toolset.
This exploratory analysis video shows how a unique language provides similar perspectives in the same dataset.
4) Steering the development of an environment that takes advantage of an ecosystem of great tools
Bestiario’s CEO José Aguirre always like to present Quadrigram as a sponge capable of absorbing information from many diverse sources: social networks, data bases, Internet of Things, social media tools, business analytics tools, etc. stressing that “In the wild we know that it is not the strongest who survive but rather those who best cooperate”. We brought that vision to reality with an environment based on severs ‘in the cloud’ that integrates with other sophisticated tools. Like many other platforms, Quadrigram connects to various types of data sources (databases, APIs, files, …) to load data within a workspace. But we also wanted users with detailed needs to take advantage R scripting to perform advanced statistical method or Gephi to layout large networks. The main challenge was to find and implement a protocol to communicate Quadgrigram data structure back and forth with these great tools. In other words, we wanted users to perform analysis in R as part of their data flow. Similar to the architecture of distributed systems and the used of JSON nowadays, the solution was to pass around serialized Quadrigram objects. That offers a pretty unique mechanism to store and share results of data manipulations, what we call “memories”. For instance the content of a Table stored in Quadrigram server is available publically to other tools via a URL (e.g. http://nfl.quadrigram.com/account/m/ext/memo/public/fabien/cosm/cpu store an analysis of my CPU activity)
Why do I blog this: It has been a unique opportunity to help shape a software product and bring it to market. When we created Lift Lab and now Near Future Laboratory we knew if was the kind of experience we wanted to live. This post is an attempt to keep track of the work performed to make Quadrigram a tool that we hope will open new practices around the manipulation and visualization of data. Thanks to the team at Bestiario for their talent and stimulating discussions. I will continue contributing to the project with constant technical, strategic and conceptual guidance. I have also jumped in the advisory board in company of Bernando Hernandez and Jaume Oliu.
Over the last year we have been collaborating with the mobile phone operator Swisscom and the City of Geneva to materialize insights on urban centralities and the connectivity of central neighborhoods with peripheral towns. The fundamentals of this project rely on measures, maps and visualizations of the pulse of the city through the activity of its mobile phone networks.
In the desire to make this work more public and raise the public awareness on the use of network data as part of urban management strategies, the Mayor of Geneva proposed to embed the data into were they are generated. To produce this ‘urban demo’ we collaborated with our friends at the Lift Conference to create an event and delivered aggregated network activity measures to the digital magicians at Interactive Things. Their evocative visualizations named Ville Vivante took the form of a visual animation and eight posters deployed at the Geneva central station from February 20th to March 4th 2012.
The visual animation
And Interactive Things co-founder Benjamin Wiederkehr presenting the project and their magic at the Lift Conference
Last week I participated to the O’Reilly Strata Conference with a 40-minutes talk in the session on ‘visualization & interfaces’. My contribution suggested the necessity to quickly answer and produce questions at different stages of the innovation process with data. I extended the material presented at Smart City World Congress by adding some narrative on the practice of sketching by major world changers and focussing on Quadrigram as an example of tools that embraces this practice with data. The abstract went as follow:
Sketching with data
Since the early days of the data deluge, the Near Future Laboratory has been helping many actors of the ‘smart city’ in transforming the accumulation of network data (e.g. cellular network activity, aggregated credit card transactions, real-time traffic information, user-generated content) into products or services. Due to their innovative and transversal incline, our projects generally involve a wide variety of professionals from physicist and engineers to lawyers, decision makers and strategists.
Our innovation methods embark these different stakeholders with fast prototyped tools that promote the processing, recompilation, interpretation, and reinterpretation of insights. For instance, our experience shows that the multiple perspectives extracted from the use of exploratory data visualizations is crucial to quickly answer some basic questions and provoke many better ones. Moreover, the ability to quickly sketch an interactive system or dashboard is a way to develop a common language amongst varied and different stakeholders. It allows them to focus on tangible opportunities of product or service that are hidden within their data. In this form of rapid visual business intelligence, an analysis and its visualization are not the results, but rather the supporting elements of a co-creation process to extract value from data.
We will exemplify our methods with tools that help engage a wide spectrum of professionals to the innovation path in data science. These tools are based on a flexible data platform and visual programming environment that permit to go beyond the limited design possibilities industry standards. Additionally they reduce the prototyping time necessary to sketch interactive visualizations that allow the different stakeholder of an organization to take an active part in the design of services or products.
Slides + notes (including links to videos)
Sketching with data (PDF 15.7MB) presented at the O’Reilly Strata Conference in Santa Clara, CA on 29.02.2012.
This week was dedicated to the Smart City World Congress in Barcelona. It was my first outing in a comfy Near Future Laboratory jumpsuit. With Nicolas, we are indeed slowly shutting down the mainframes at Lift Lab and relocating our immaterialities to the Near Future Laboratory facilities. These things take their good share of time and energy, but we are pretty excited to merging our operations with a new gang of scouts dispersed hither and yon. The event collided with two other important milestones of projects steered these past few months.
First our client BBVA, presented publicly some of the measures and indicators of commercial activities in cities we have been producing and investigating. The visual supports of this project take the forms of maps (pdf), dashboards, and tools that each reveal a city and its quantified streets under new spatio-temporal lights.
Second, my peeps at Bestiario have working endlessly to release Quadrigram, a tool for individuals and organizations that work intensively with data and information. We are now running in private beta. More on that later.
So, in the margin of the multiple discussions on the definitions of a *smart* city, I could not help but contribute to the congress with my experience on the field in making urban data work. My discoursed focused on the necessity to treat data as a living material that must be crafted and manipulated at the different stages of knowledge and service production. I name that “sketching with data” and as with any creative work with digital technologies, it comes with tools and an undisciplinary process. Here are the slide deck + notes of my talk:
Sketching with urban data (PDF 6.9MB) presented at the Smart City World Congress in Barcelona on 29.11.2011.
In the audience, Alexandra Etel Rodriguez, Partner at Connected Brains produced visual notes of my talk. Thanks Alexandra for sharing this graphic recording!
Thanks to the organizers for the invitation!
There is this influential dispatch “Follow Curiosity, Not Careers” by Julian Bleecker that I love to refer to. In a few paragraphs he argues for the importance of shifting ones practices and area of activity of 3-5 years cycles. Cycles that are driven by curiosity with phases that link sometimes consciously and sometimes in unplanned and disruptive manners.
Two years ago, I engaged into a Making/Creating/Building phase after the feeling that my “voice” of my academic journey needed a renewal. At that time, I was shaping a project for the Louvre on the evolution of “hyper-congestion” levels in key areas of the museum. An investigation directed at the urban informatics era when few people had experience of actually working with local authorities or decision makers on a large scale that affect either governance or built fabric (reminding me of Dan Hill indication of shortcoming of the Microsoft Research Social Computing Symposium 2010).
At the Louvre experimenting with sensors to measure levels of hyper-congestion.
Since then, I have persisted working on the ground, observing clients and partners practices, responding to opportunities and glitches with new data tools and experimenting with research methods. I was particularly focused in understanding how the exploitation of network data could integrate and complement traditional processes. It means confronting my evolving practice, plotting in unknown territories, or tinkering the business and financial aspects of a product “go to market” strategy. The phase has been extremely enriching that I only start to grasp coherently. Along the path, I got to lead the making/creation/building for the multiple actors of the ‘smart city’:
- A geographical information provider: a GIS model that generate a novel type of street data based on social media content for cities with very limited information layers.
- A real-time traffic information provider: innovative indicators and interactive visualizations that profile the traffic on key road segments.
- A multinational retail bank: co-create its role in the networked city of the near future with a mix of workshops and tangible results on how bank data are sources of novel services.
- A large exhibition and convention center: with audits based on sensor data to rethink the way they can manage and sells their spaces.
- A mobile phone operator and a city council: to measure the pulse at different parts of the city from its cellphone network activity and extract value for both city governance and new services for citizens and mobile customers.
- It has been equally important to independently explore the ideas shared at Lift Lab either through academic collaborations with UPF, MIT, EPFL or through the actual experimentation of services like elephant-path.com that I would love to develop more.
Today, my trousers are scuffed. This accumulated experience on the field requests a move to a next phase to what Julian would describe as:
And subsequent years, refining and polishing that “voice”. Keep moving, refining, finding ways to continue to learn and bringing all the other bits of learning, the other “fields”, the other ways of knowing and seeing the world, all the other bounded disciplines — let them intrude and change things.
Practically, I will continue to push Lift Lab in imagining fast-prototyping ‘stuff’ and explore their implications as a core element our investigation. But the most exciting feeling is that I can start polishing a “voice” in company of a growing list of friends I admire who now run their own boutiques/studios/collective/structure to operate on the field and practically contribute in shaping the urban near future. They are the Bestiario, Urbanscale, City Innovation Group, Everythng. We share an approach that dramatically contrast with the data-driven ‘smart city’ marketing ploy. We come from practices that integrate the importance of learning from both history and fiction, that understand the implication from the long-running theoretical and practical challenges of using data to improve urban life. We are aware of the shortcoming of data models (see The “Quants”, their Normalizations and their Abstractions), we experimented the value of Mixed Methods and are becoming fluent in both design and research approaches as sources of knowledge as so elegantly described by Kevin Walker Design Research and Research Design.
The shift of phase comes naturally with attempts of finding coherence in the contributions of the last two years or simply “polishing my practice”. So practically: I have been exploring the exploitation of network data (byproducts of digital activity) as material to qualify the built environment and produce new insights for the different actors of the urban space (e.g. city governments, service providers, citizens). These stakeholders have approached Lift Lab to a) find unknown benefits in data they already exploit or b) investigate specific problems they instinctively feel network data will help them solve.
There is one specific methodological aspect to emerge from my work. A year ago, I described it as “Sketching with data“. I found it extremely useful to go beyond the traditional ways of sharing the exploration of network data and avoid the contemporary experience with data as described in the recent review of the IBM’s “Think” exhibition in New York.
“But we get no practical sense of how traffic information might be useful.”
“It would have been far more powerful to have an interactive display that led viewers on a path of interpretation and mapping, so we could experience the process instead of simply sampling images. “
The exhibition is actually quite insightful and I value the effort of IBM to communicate. However in projects involving multiple stakeholders, the ability to rapidly sharing interactive information visualizations is a key practice to transform information into a tangible and imperfect material. Recently I attempted to describe it in an abstract submitted to a practitioners’ conference sub:
Since the early days of the data deluge, Lift Lab has been helping many actors of the ‘smart city’ in transforming the accumulation of network data (e.g. cellular network activity, aggregated credit card transactions, real-time traffic information, user-generated content) into products or services. Due to their innovative and transversal incline, our projects generally involve a wide variety of professionals from physicist and engineers to lawyers, decision makers and strategists. Our innovation methods embark these different stakeholders with fast prototyped tools that promote the processing, recompilation, interpretation, and reinterpretation of insights. For instance, our experience shows that the multiple perspectives extracted from the use of exploratory data visualizations is crucial to quickly answer some basic questions and provoke many better ones. Moreover, the ability to quickly sketch an interactive system or dashboard is a way to develop a common language amongst varied and different stakeholders. It allows them to focus on tangible opportunities of product or service that are hidden within their data. In this form of rapid visual business intelligence, an analysis and its visualization are not the results, but rather the supporting elements of a co-creation process to extract value from data. We will exemplify our methods with tools that help engage a wide spectrum of professionals to the innovation path in data science. These tools are based on a flexible data platform and visual programming environment that permit to go beyond the limited design possibilities industry standards. Additionally they reduce the prototyping time necessary to sketch interactive visualizations that allow the different stakeholder of an organization to take an active part in the design of services or products.
Sketching with mobility data in Impure
Why do I blog this: The idea of shifting ones practice and area of activity is quite important to me. It comes with phases similar to the pursue of a PhD (listen, propose, experiment, contribute with a voice, confront the contributions). The shift of phase is sometimes planned and sometimes affected by external event. This polishing phase occurs with pleasant evolutions the name, structures and focus of Lift Lab. More on that later…