WORM, A VISUALISATION ENGINE for THE INNER STRUCTURE OF RACING

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1 WORM, A VISUALISATION ENGINE for THE INNER STRUCTURE OF RACING Dr Amer Salman, Mr Emiliano Rodriguez Nüesch, and Mrs Rula Salman College of Music & Media and Creative Technology Thames Valley University, Ealing, London, W5 5DX,UK Tel:++44 (0) amer.salman@tvu.ac.uk, enuesch@hotmail.com, rula.salman@yahoo.com Abstract Formula One races have the greatest media impact among car racing. It is estimated that the seventeen races of the 2000 season attracted over 53 billion television viewers, whilst the printed press maintained a significant presence, with an average of 650 journalists and photographers from 65 countries travelling from all over the world to cover each Event [3]. The present work provides a visualization engine for Formula One races, a practise highly dependent on data generation and processing both for the TV audience to be able to make sense of it, and for the teams/drivers to develop real time strategies. The developed tool allows the users to interrogate data generated from races, in particular the relationship between cars performance and changes in positions lap after lap, and how the sum of relative values from each car reflects the inner dynamics of a racing. The beauty of WORM, the visualization engine, is that it allows the users to construct their own visual race, re-ordering the different cars according to the individual data exploration needs. Keywords: Visualize, re-order, interrogate, data, performance, position, formula one 1 INTRODUCTION In the following 3 years more data will be generated than in all previous human history [7]. Not only is there an overload of it, but it will be too abstract to use. The problem is, then, how to make sense of all this data. This is why it is necessary to develop models and tools that would turn raw data into usable and meaningful information which enables the users to make decisions and predict future events. First of all, we would like to distinguish between information design and information visualization. Information visualisation is "a visual representation of data to amplify cognition"[4], information design is "the process of creating this visualization" [4], which means that Information design is about filtering, reordering and assigning visual properties to data. The visualization, then, is the visible result of this operation with its own representational logic. Both levels together constitute an intelligent lens, through which raw information translates into your own visible language [8]. According to Nathan Shedroff [11], an experienced designer from California, data can be turned into information through organization. Organising data in a meaningful way would allow the user to relate the microscopic observation of detail to a context that makes them relevant. This led us to think of how complex it was in the mind of the user (and the racing audiences in general) to keep track of that ever changing lists of positions and timings during races. But what is a Formula One race? Twenty-two cars normally have to complete around 72 laps. The distance of a race (Grand Prix) is the least number of laps which exceeds 305 km, but no race may last for more than two hours [3]. 2 COMPLEXITIES AND PROBLEM DEFINITION We are particularly interested in Formula One racing because of how heavily it relies on data generation and its processing. It could be said that without time measures and real time statistics there would be no race. For the TV audience, Formula One racing is mainly a media event, it is impossible to make sense of a race without the statistics on top of the video signal showing positions, evolving time/distance between drivers, lap numbers, etc. In parallel, the strategy of teams and drivers is pretty much about data processing as well. The continuous dialogue between the driver and the team manager during the race proves this. This is another level to the importance of data

2 during a race, the processing of data affects the development of the race s real time. In spite of the available statistics and analysis it is still very difficult to make a mental image of what the structure of a race looks like, and how it evolves through time. The multiplicity of perspectives and cameras makes it even more difficult. This makes it more challenging as well, because of the potential for enriching data visualizations with moving images is huge. What strikes us the most about racing is that the whole story of a race is a collection of mini-stories. Each car s story does not necessarily share the same space and time co-ordinates with the rest. For example, the leader can be behind the car in position seven being followed by the car in position eighteen. This is the result of the interaction of cars going round in circles. it is very difficult to examine in order to draw conclusions. We understood that data has dimensionality [13]. In our case, the dimensions of data are: 1- Time 2- Position 3- Driver 4- Lap The four are closely interrelated with a continuous changing relation throughout the race. These dimensions belonged to three different types of data: numerical, ordinal and categorical [12]. The data will not always be numerical, though much of it is. It can be ordinal, as with things that are naturally ordered (such as the days 3 WORM ENGINE THE SOLUTION WORM aims to be a solution to understand complexity. It is necessary to interrogate data in many different ways, and to understand the relationship between stops, car s performance and the differences between teams or circuits during the race. WORM addresses another complex aspect of racing, it is easy to forget which were the original positions, making it difficult to identify trends in changes over time. Visualisation design reconstructs all the pieces that the normal development of a race creates and spreads all around the circuit through using a single visual unit. In addition, users would be able to apply the engine to visualise the variety of results collected by the measuring technologies like TAG HEUER s [6]. This work would help teams understand patterns in a race from any member of the team s perspective. We will describe those patterns and the possibilities of such tool. 4 RAW DATA: UNDERSTANDING, STRUCTURING AND ANALYSIS There are two datasheets for each race. In this case we have used the Brazil Grand Prix [3] generated by Tag HEUER s [6]. Fig(1) shows part of the first datasheet. Driver names, laps and times are the main elements. Fig(2) shows part of the second datasheet. Driver names, laps and position are the main elements. From the beginning we realised that analysis of data would be very time consuming as Fig(1) Part of first datasheet of the week), or categorical, such as the names of animals where there is no order (for example, horse, zebra, antelope) [12]. After considering Bertin s re-orderable matrix [1], it was an important issue to arrange the categorical data allowing the users to keep track of initial positions all along the race representation. The main interest was to combine both datasheets in a meaningful way to be able to look for hidden relationships in the numerical data sets. The aim would be to show the relationship between each car s performance and its changes in position. For example, when a car is performing better, it maybe advancing its position. 5 ANALYSIS OF RELEVANT STUDY Our research found three relevant studies that are worth mentioning. We have given our own name for each one.

5.1 Formula One Result In addition the movement of worms may have interesting similarities with the way the relevant data moves from one car to the other, and how they call attention to each other. 6.

3 5.1 Formula One Result In addition the movement of worms may have interesting similarities with the way the relevant data moves from one car to the other, and how they call attention to each other. 6.2 Basic Theory for Interface Different issues were considered prior to the final design of the interface being made Information Representation Issues Fig(2) Part of second datasheet, where column G shows lap numbers The typical way, in which data from a race is portrayed with a list of drivers, positions and times. This list is updated lap after lap, but it is difficult to keep track of the changes, therefore it is impossible to keep a mental image of the race throughout [3]. 5.2 Interactive Graphics This study shows performance lap by lap in relation to the winner s average. On demand details like images and positions were available. The advantage of this study is to show the race in one view. The limitation was that some levels of its inner structure are not shown especially the relevant relationship between a car s performance and positions lap after lap, which makes it a point of disadvantage [10]. 5.3 Forix Graphics Designed by Michele Merino and Joao Paulo Cunha Da Silva [3]. The disadvantage to this study is that it does not show us the relationship between each car s performance one lap at a time. 6 DESIGN AND IMPLEMENTATION 6.1 Worm The Name The work is named WORM for various reasons. The line of cars during a race often looks like an emerging worm. In this sense the representational level would have the properties of the real race. This research at the representational level was focused, on the one hand, in choosing the appropriate and most flexible modes. On the other, in defining which visual properties would best convey the data properties. Martin Dodge, in his book Mapping Cyberspace [2] describes four different types of mapping or representing information: Mapping can take one of four forms: static, animated, interactive or dynamic. Static mappings are the equivalent of traditional cartographic maps in that they are snapshots in time. The difference is that they vary in the visualisation technique, for example extending to three dimensions. Animated mappings portray a sequence of static maps to provide times series. Interactive mappings moved beyond static mappings so that the user can move through and interrogate the map from different viewpoints. While the map itself is static, the user becomes dynamic. Dynamic maps are where the mapping automatically updates as the information used in its construction is updated. These forms of mapping can be combined so that a map can be static and interactive or dynamic and interactive [2]. Dodge s distinction helped to identify different levels of representation for our race datasheets. The strength of static representation would be useful to give the user all the time needed to analyse the data in one lap. As a snapshot in time it would be a pause in the representation. On the other hand, the animated would be useful to show how the race evolved through time. This way, we became aware that a combination of static images and animated images would be useful to enrich the visualisation. As for the dynamics of the WORM Engine the main intention was to make it highly powerful and usable through retrieving data from other races without any manipulation by the user. The data dimensionality issue was dealt with through the use of colours and various sizes

4 of a circle shape to represent how well a driver is achieving Usability Issues In traditional media, the author is in charge of selecting, encoding and presenting the material and data in almost any form of media or expression. However, in interactive media, users are becoming more and more the authors of the works. Through gaining control over the database [12], they are able to actively participate in making sense out of data, in its selection, encoding and presentation. Tools have to be flexible enough so as to allow users to re-order and choose different displays in the exploration of data. In the words of Bertin, one of the most famous information designers: A graphic is no longer drawn once and for all, it is constructed and reconstructed (manipulated) until all the relationships which lie within it have been perceived. A graphic is never an end in itself, it is a moment in the process of decision making [1]. Hence, the WORM engine has a flexible mechanism with many possibilities, which enables the user to make different meaningful analyses and useful representations rather than having a fixed type of representation. We decided to include a three-step process to visualise the race: Visual data exploration usually follows a three step process: overview, zoom and filter, and details-on-demand. In the overview step, the user identifies interesting patterns. Through zoom and filter, he focuses on one or more of them. Finally, to analyse these selected patterns, the user drills down to access details of the data [7] The Interface and Execution WORM is programmed to retrieve data from external files from any race. The tool is programmed in Macromedia Director using Lingo and it is 100% dynamic. From the user s perspective, all that is needed to execute the file is to have the Shockwave Player installed in the computer. The interface consists of a display panel where circles can be arranged and re-arranged, and a toolbar with which the user can either animate the whole race or analyse each lap at a time. All the content in the display panel -title for the race and drivers names- are 100% dynamic and retrieved from the datasheet directly. There are two possibilities to run the race. One is the automatic animation, and the button animate race is in the panel to trigger it. The other option is Dynamic to allow the users to move manually lap by lap at his/her desired speed. The buttons previous lap and next lap allow the user to do that. 6.3 Worm s Visual Intelligence Circles and Sizes for Position WORM creates a circle for each car in the race, the representation portrays their appearance with an attribute of how the car is accomplishing. They go in loops. WORM then reads the position of each car and assigns a size for the circle. The first car is the biggest, and the last one is the smallest. In the starting grid WORM would not have a colour assigned, because they haven t moved yet. Changes in positions will be represented then as changes in sizes Circles and Colours for Performance WORM calculates an average for each lap, and compares that average with the time for each driver for each lap. The result is a list of positive and negative values for each one of them. Positive values belong to cars that are achieving better than the average. Negative, for the ones who are doing badly. WORM translates these values into the green and red palette. If a car is bright green, it is doing very well in that lap in relation to the rest of the cars. If it is bright red, it is doing badly, always in relation to the rest in that lap. The cars that appear white or near to the white colour, are performing near the average Fig(3). WORM is already translating performance and position into colour and size. But the user can also construct his/her own visual race interactively Static and Interactive implementation of Worm Engine The Static implementation of WORM allows the users to move manually lap by lap at his/her desired speed, by the use of the previous lap and next lap buttons. The important thing is that unless the user decides to move it, each circle stays where it is during the whole race, so it is possible to compare throughout the race how each car has done with respect to its original position.

5 The user also has the power to re-arrange the circles to interrogate data in different ways. This rearrangement represented the first operation on the categorical data -the drivers list-. The goal was to let the user be in control of the database. For example let us consider Fig(4), the user wants to compare how a pair of teams are relate to each other. This is relevant because there is a special championship for the teams called the constructors championship. In the image we can observe how each team is performing compared to the rest Animation and Dynamic Implementation of WORM Engine The animation in WORM is an illusion of movement, and its goal is not only to make apparent changes in positions but also to allow the user to construct a mental image of the race occurring over time. In addition, animation could play an important role in making all of the comparisons more meaningful. One possibility to start the race is the automatic animation, and the button animate race is in the panel to trigger it. The Dynamic implementation of WORM engine allows retrieving data from different race for analysis. 7 EVALUATION AND CONCLUSIONS 7.1 Evaluations WORM has many different uses. We asked 10 different people to look at our work, evaluate it, and compare it to those used by TV, and other visualisation systems. Comments written by Dr Sebastian Uchitel, (Imperial College, Computer Science, in London), give a brief summary of the evaluation: Formula 1 racing as seen on TV is like watching a rally. You get to see each car individually, but rarely get the feeling of drivers competing between each other. Statistics shown on TV screens are too static, only giving information that is updated lap by lap. However, using this digital tool, and seeing all circles together growing and changing colours gives you a feel of what is going on in the race as a whole. In addition, you can keep track of the drivers and the relations between them that you are interested in, rather than seeing how the Ferraris are doing compared to the rest. 7.2 Conclusions We found that our work has made the management of car races much more intelligent and we have designed a tool that is flexible and useful for many different uses. One of the beauties of WORM Engine is that the engine retrieves time values, but time is not represented in the visualization. This is a strong design decision that emphasises the relevant differences between cars. The tool is interesting in a sense that it reveals patterns in a race in comparison to different circuits. In some circuits it is much more difficult to overtake cars than in others, this visualisation is a useful tool to analyse such facts. WORM is very efficient in detecting anomalies in data. For example Fig(5), in lap 13, shows all cars in bright green, except for one. The latter appears in red, this gives the user the instant possibility of identifying specific events in data. This means that this particular car has performed so badly that all the rest are well above the average. The real value in the datasheet is that the driver took 600 seconds to complete that lap, while the rest of the drivers took between 70 and 80 seconds. One way of inducing an emotional connection with a quantitative representation is by developing some sort of emotional qualities. A WORM may invite the user to create different types of personal and emotional connections by creating his/her own relevant race WORMS. Finally, WORM is an interesting tool to analyse the effect of car stopping strategies on the performance and positions relative to the cars that do not stop. A car stop will effect not only the performance in one lap, but will have an effect on the rest of the race as well. 8 FUTURE IMPROVEMENTS Our opinion is that this research has just begun. Some of the future improvements for WORM will be: The possibility of writing comments on each lap and then being able to save the whole race with the comments. WORM would then become a diary for the user with analysis of each race. On demand details. Following Keim s [7] description of interaction in visualisations the real time value each car took to complete each lap will appear when rolling over the mouse on top of each circle. 9 SNAPSHOTS OF WORM This section gives snapshots of WORM that are discussed in this work.

10 ACKNOWLEDGEMENT We wish to express our appreciation to Liv Franzen for the help with Lingo programming, Joao Paulo Cunha in FORIX for letting us use some of his databases for the races and

11 REFERENCES Fig(3) Performance and position representation of WORM Fig(4) Example of static and interactive representation of WORM [1] Jacques Bertin. Graphics and graphic information processing.

Mapping Cyberspace, Routledge, p72,2001 [3] FORIX (Formula One Results and Information explorer) http://www.forix.com [4] Benjamin Fry s MA Thesis. Organic Information design, 2000.

6 10 ACKNOWLEDGEMENT We wish to express our appreciation to Liv Franzen for the help with Lingo programming, Joao Paulo Cunha in FORIX for letting us use some of his databases for the races and comments provided by Dr Sebastian Uchitel, (Imperial College, Computer Science, in London). 11 REFERENCES Fig(3) Performance and position representation of WORM Fig(4) Example of static and interactive representation of WORM [1] Jacques Bertin. Graphics and graphic information processing. Translated by Walter de Gruyter, William J.Berg and Paul Scott. [2] Martin Dodge and Rob Kitchin. Mapping Cyberspace, Routledge, p72,2001 [3] FORIX (Formula One Results and Information explorer) [4] Benjamin Fry s MA Thesis. Organic Information design, [5] Nahum Gershom and Ward Page. What can storytelling do for Information Visualization. Communications of the ACM, Vol. 44 No8, p 31-37, August 2001 [6] Tag Heuer web site [7] Daniel A. Keim. Visual exploration of large data sets. Communications of the ACM, Vol 44, No 8, p39-44, August [8] John Maeda. Media. Thames & Hudson, London 2000 [9] SmartMoney map of the market by Martin Wattenberg [10] Emiliano Rodriguez web site erformance.html [11] Nathan Shedroff, Information designs: Unified field theory of design from Information Design edited by Jacobson. MIT press, 1999 [12] Robert Spence. Information Visualization, ACM Press, 2000 [13] Edward Tufte. The visual display of quantitative information, Graphics Press, 2001 [14] Williams website Fig(5) Detected data anomalies by WORM

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