META4ACLE: GENERATING COMPELLING METAPHORS FOR ...

Proceedings of the 20th International Conference on Design Theory and Methodology DTM 2008 August 3-6, 2008, New York City, New York, USA

DRAFT

DETC2008-49331 META4ACLE: GENERATING COMPELLING METAPHORS FOR DESIGN Erik M. W. Kolb1 University of Technology RWTH Aachen Deutsche Post Endowed Chair of Optimization of Distribution Networks Templergraben 64, 52056 Aachen, Germany [email protected]

Jonathan Hey University of California at Berkeley Berkeley Institute of Design 354/360 Hearst Mining Building, Berkeley, CA 94720, USA [email protected]

Hans-Jürgen Sebastian University of Technology RWTH Aachen Deutsche Post Endowed Chair of Optimization of Distribution Networks Templergraben 64, 52056 Aachen, Germany [email protected]

Alice M. Agogino University of California at Berkeley Berkeley Expert Systems Technology Lab 5136 Etcheverry, Berkeley, CA 94720, USA [email protected]

ABSTRACT Metaphors have successfully been used by new product development and design teams to help frame the design situation and communicate new products to stakeholders. Yet, the process of finding a compelling metaphor often turns upon stumbling upon it or a flash of insight from a team member. We present Meta4acle: a Metaphor Exploration Tool for Design that suggests possible metaphors to make the process of finding a metaphor more one of "seeking out" than "stumbling upon". The tool takes data about the project in the form of a title, domain and key associations required of the metaphor and returns suggestions from a database of possible metaphor sources. We built a Meta4acle prototype and evaluated it with positive results for three existing design case studies. We present plans for its full implementation and evaluation. Keywords: metaphor, design tool, reframing, design methods, product design, concept phase 1 1.1

MOTIVATION

Study purpose and research goal The human-centered design process [1] is being recognized for its success in creating products that meet

people’s real needs. Yet, designers of these products face a difficult challenge in getting to know their eventual users, their needs and the broader design context. In many projects, metaphors, understanding one thing in terms of another, have been reported to help designers frame their design situation and develop products that resonate with their users, for example, the famous advertisement of the Apple Macintosh as “A Bicycle for the Mind” [2]. While the rhetoric surrounding metaphor use is generally enthusiastic (with some notable exceptions, for example [3]) few researchers or designers have proposed structured means to incorporate metaphor effectively in the design process and the methods proposed have not received widespread adoption. As a result, the use of metaphor in design across most design schools and practice remains haphazard. In documented cases of the use of metaphor it is difficult to reconstruct the process used by the designers to find the metaphor. In many cases it seems that the designers stumbled upon a great metaphor by accident or it suddenly came to them in a flash of insight. But what if insight does not strike and teams do not stumble upon a compelling metaphor? We began this study with the goal of transforming the stumbling on to the seeking out of a compelling metaphor releasing designers from

1 Part of the work has been performed during a research stay at the University of California at Berkeley in the Berkeley Expert Systems Technology Lab.

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relying on the uncertain arrival of inspiration or luck. Our primary research goal is to: Develop a tool or method for systematically seeking out compelling metaphors for use in design projects 1.2

Metaphor use in design We use metaphors to understand one concept in terms of another. Most people are familiar with metaphors from writers who routinely employ metaphor to enhance the vividness and clarity of descriptions such as Shakespeare’s famous opening: To be, or not to be: that is the question: Whether 'tis nobler in the mind to suffer The slings and arrows of outrageous fortune, Or to take arms against a sea of troubles, And by opposing end them? Yet metaphors are also applied more pragmatically. Schön describes a case where a design team changed to thinking of a paintbrush as a pump for paint rather than as a spreader [4]. The metaphor ‘Paintbrush Is A Pump’ helped the design team move forward with a new framing of their design situation. Careless metaphor choice can also lead to serious problems as in Saffer’s example of Banking Is A Game in the design of an automatic teller machine [5]. The metaphor is problematic as it connects associations like risk and fun with serious bank service; it might lead to ideas of gambling and potential loss of money. Metaphors are not limited only to written or spoken language, but may include, for example, images. In language similes can also be metaphors using the slightly different syntax of like or as, for example, “the paintbrush is like a pump.” Metaphors are often confused with analogies, yet while an analogy neatly maps causal structures between two domains, for example, the wing of a plane and the sail of a boat, a metaphor provides more flexibility in use without being restricted to the causal or physical mapping. For example, the two concepts in the metaphor The Cafeteria Is An Oasis share some key associations yet also provide possibilities for new structure not in a causal mapping. More recently, Nicholas Negroponte, discussing the development of the $100 laptop project explained how they plan to reduce the market for selling stolen laptops – the gray market. He explained that, “One of the ways to help in the case of the gray market is to make something that is so utterly unique. Thousands of automobiles are stolen every day in the United States, [but] not one single Post Office truck is stolen. Why? Because there’s no market for Post Office trucks. Thus even you paint it or modify it, it still looks like a Post Office truck and won't be sellable. The metaphor, The Laptop Is A Post Office Truck, clearly communicates how to design the laptop to reduce gray market sales [6]. A well known example of metaphor use in design is given by Nonaka, who shares an account of how the Beer Can Copier metaphor helped the Canon design team to come up with a mini-copier that created the personal copier market that led

Canon’s successful migration to the lucrative field of office automation [7]. Yet, what ties these examples together? What makes an effective design metaphor? Metaphors are commonly used in two different ways. A metaphor can be descriptive – helping understand the current reality – or prescriptive – helping point the way forward to new solution directions. Both types of metaphors have value for communication and how well a metaphor resonates with stakeholders is one criterion. Descriptive metaphors need to closely match the current reality to make sense. Prescriptive metaphors need to help inspire designers with new ideas. Metaphors have greater impact when they help designers reframe a situation, to view it from a new point of view, highlighting previously hidden aspects. With these different criteria it is rare that one metaphor will satisfy all situations. Yet, to be an effective metaphor, they must at the least help meet one or several of these criteria. It is also important to draw a distinction between concepts and the words, or terms, used to describe them. In the language of semiotics the term is the signifier, the form which a sign takes, in this case a combination of letters, that points to the signified, the concept it represents [8]. For example, car, the word is the three letter combination c-a-r, whereas the concept is what is brought to mind, the vehicle that you drive. Confusion is possible when the same signifier points to more than one concept, when the same word has different meanings. As this is not something we can change it is something we have to design for. Just as the choice of words to communicate with has to make sense to the people it is intended for, a well chosen metaphor therefore has to be carefully suited to the recipients; a metaphor will not be appropriate for all. 1.3

Design Scenario How can a design team consistently find a useful metaphor for their project? We were motivated by helping design teams reduce their reliance on chance or inspiration. The following hypothetical scenario illustrates the kind of team experience we hope to enable. A design team was tasked to develop a new line of office furniture. Insights from their user research suggested that employees enjoy working at home, but lack the productivity of the office. Yet at the office the employees miss the stimulating and creative environment of the home. The new line of office furniture needs to somehow bring the benefits of home working to the office. The design team identified some key user needs but is struggling to move forward in the design process – each person on the team has a different vision of what they should be developing and they struggle to talk about their project direction because there is no similar existing project. They hope to find a metaphor to unify their different visions of the project and suggest ways forward. At a design meeting, John, the project leader, projects the metaphor design tool on a large screen. Together the

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team inputs the name of the project as well as the needs and some of their most compelling stories from their research regarding the home and the office. The tool then suggests a range of possible metaphor sources that the team is able to refine, discuss and select. Happy with the possibilities, the team prints out some results to explore with around a table. Among others, the tool suggested thinking of the Furniture As An Ants Nest2, Favorite Song3 or Kids TV4. The metaphors helped the team talk about the project on common ground as the project progressed and led to several exciting design ideas. 1.4

Structure This paper describes the development of a similar tool to that our fictional design team used: Meta4acle. In the next section we first discuss past research on metaphors in design. In section 3 we present the design of the tool’s technical approach and user experience. Section 4 discusses the implementation of the tool and its preliminary evaluation on three design case studies before we present our conclusions and future work. 2

BACKGROUND

2.1

Literature review As the implementation of the Meta4acle is our final goal the research review is structured first by literature on early phase design methods, conceptual metaphor, metaphor use in design, metaphor design methods and computational approaches to metaphor generation. 2.1.1 Design methods for early design stages Consider the following standard phases of the design process [9]: Concept development System design Detail design Testing and refinement Production ramp-up In later phases design flexibility decreases dramatically as costs are committed through early design decisions. A window of opportunity therefore exists to significantly affect product quality with careful decisions in the early phases [10]. Concept development is often divided into problem definition, or identifying a design opportunity, and concept generation. There is a wide range of techniques used for concept generation including, Brainstorming, where a team tries to come up with new ideas focusing on quantity, 2

Ants nests unify all needs in one place; work and living, colleagues and friends, as well as food. 3 A favorite song triggers positive feelings and motivates creative working, thus merging positive emotions with the current action. 4 A Kids TV combines the feelings of comfort, fun and learning at the same time.

suspending judgment, encouraging wild ideas and building on each others’ ideas. Other structured approaches straddle both problem definition and concept generation such as: Analogy where designers try find a analogous solutions to their problem and transfer solution principles [11]. TRIZ uses patterns identified from design solutions from the patent databases to make creativity a more “exact science” [12] [13]. There are many TRIZ methods but key steps include identifying contradictions, using inventive principles previously used to solve these contradictions, and searching a large database of physical effects and phenomena. Other approaches for early stage design include the use of design repositories. Many engineering problems recur frequently, therefore engineers and designers can benefit by reusing existing solutions. In a similar approach to that of TRIZ, design repositories organize design solutions by functional and conceptual content allowing access to past solutions or parts of solutions [14]. Suh’s axiomatic design approach [15] is an analytical method that uses the concepts of maintaining independence of functional requirements and reducing the information content of the design to systematically transfer from customer needs to design specifications. The core method tries to eliminate couplings between multiple functional requirements and multiple design parameters. The Synectics creative problem-solving method explicitly provides a method for employing metaphor for problem definition [16]. The approach encourages team members to find metaphors embodying key features of the problem from distant domains to encourage creative connections. While the method certainly encourages effective metaphor use it relies upon the knowledge and experience of those in the problem-solving team to make appropriate connections and find relevant metaphors. While each of these approaches have their own merits none of them provide systematic methods for employing metaphors in design or the ability to tap into a pool of knowledge larger than the current design team to find appropriate metaphors. As a result, metaphor use remains both haphazard and inefficient, reducing its widespread adoption in design practice. 2.1.2 Conceptual metaphor5 Metaphor (from the Greek metapherin meaning to transfer) is a device that compares apparently unrelated subjects. Metaphor is used to understand one domain in terms of another. The theory of conceptual metaphor argues that metaphor is critical to our reasoning about everyday concepts such as love, time, ideas and solutions [17]. Metaphors are commonly written with the title case typographical convention Target Is Source. The source domain is the conceptual domain from which we draw metaphorical 5 Kövecses book, ‘Metaphor’, is a detailed and varied introduction to conceptual metaphor [50].

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expressions and the target domain is the conceptual domain that we try to understand. For example, in the metaphor Ideas Are Objects, Ideas is the target domain – the abstract domain we are trying to understand – and Objects is the source domain – a concept we are largely familiar with. The choice of metaphor helps us understand a concept in a different way. For example, thinking of Ideas As Objects leads to being able to “bounce a few ideas around.” An alternative metaphor, such as Ideas Are A Spectrum, makes the very concept of bouncing an idea problematic. Because of its power to provide a new perspective on a concept, metaphor can play a large role in reframing a design situation. 2.1.3 Metaphors in design Metaphors find their most active application in the area of user interface design because designers need to make the abstract, intangible and seemingly magical operations of computing understandable to users. Early uses led to enthusiastic adoption and the design of software with a strong common metaphor – for example, designing online shopping software as a shopping mall where users have to navigate from shop to shop [3]. Abuse of metaphor has had some outspoken critics such as Cooper. The reason for many of these failures is that successful metaphors are based on concepts we already know about – like shopping in a shopping mall or city center. Yet, the advantages of software and computing is precisely that it allows us to do things that aren’t possible in the physical world. As a consequence when software is designed around a strong metaphor it often serves to limit what is possible when using the software, and at worst it confuses. For example, instantly transporting oneself to a new shop with one click is simply not possible in the physical world, and the bookmark metaphor for web browsers quickly breaks down when the number of bookmarks becomes large and requires organizing. Despite these potential disadvantages, Stubblefield [18] found that, although a metaphor in use by a software design team didn’t eventually inspire the final form of the software, it can benefit design teams throughout the process by providing a common basis for communication. More so than in physical products, software products will continue to use metaphors to explain the intangible operations of a computer be it in the form of web pages, a lasso tool, or a search engine [19]. Metaphors also find application in the physical form of products by industrial designers and mechanical engineers trying to evoke feeling or deeper meaning through a metaphor. For example, the Motorola Pebl phone [20], builds off a pebble metaphor with its “Iconic oval-shaped design with elegant silver finish…” The pebble metaphor evokes an accessory of natural beauty with a shape, weight and texture that feels good in the hand. 2.1.4 Metaphor design methods In addition to the Synectics method, a few authors have proposed methods to incorporate framing via metaphor into the design process. Madsen’s [21] guide to metaphorical design

provides a structured approach built off the careful analysis of interviews with key stakeholders. Madsen’s sensible approach relies on the designers analyzing the metaphors used by the interviewees about the design of a computer system. In this sense it is better suited to an understanding of the current situation rather than to finding a metaphor to create a new reality or prospective physical product. A number of other commercial firms, such as IDEA Champions [22], sells ‘manuals’ for finding metaphors to generate new insights and inspire ideas. These approaches typically follow the stages of: identifying problems or features of your problem situation; finding a different but related situation; finding pairings of the features in your situation with the related situation; and finally, employing solution strategies from the related situation to solve your own problems. While these manuals certainly help to structure a process they provide little support for the hardest stage of finding an appropriate metaphor with the right characteristics, nor are they explicitly designed to be performed as a team. 2.2

Database and algorithm review

2.2.1 Metaphor databases Prior work establishing databases of metaphor for either reference or metaphor generation is somewhat sporadic and incomplete. Several online tools exist. The Conceptual Metaphor WWW server at Berkeley is a research tool for cognitive scientists and others interested in the study of conceptual metaphor systems [23]. Unfortunately, the database is no longer maintained. The Hamburg Metaphor Database project [24], is an online database of French and German metaphors which came into being in 2002. Its collection of general metaphors serves the purpose of language studies. Its primary use is to investigate cross-language comparison of metaphors. Princeton University’s WordNet database has been the starting point for many linguistic tools. Lönneker [25, 26] performed an analysis of metaphors from the widely used WordNet database. The intent was to enrich the database with metaphor information. Unfortunately, the different motives in the creation of each of these databases made each unsuitable starting points for developing a tool for designers. 2.2.2 Conceptual design databases Other related tools in the field of design research include conceptual design databases. These databases, including casedbased design, are intended to help designers by tapping into a wealth of previous design cases. In general, the process is to understand your problem in abstract terms that can be used to search the design database, and then review the cases that match your situation. For example, Bohm [27] describes the exploration of a design repository system. They are pushing the capability of repository systems closer to autonomous concept generation.

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Their research explores case-based reasoning in design. Some earlier work on case-based design was done for example by Wood and Agogino [28], who explored an integrated approach including marketing, design, manufacture, distribution, operation, and disposal. Commercial tools also exist including the Goldfire Innovator software [29]. Goldfire Innovator extends the design database concept by utilizing existing design solutions from patents and also including a company’s own design solution experience. In a similar vein are software including I-TRIZ [30] built around the TRIZ methodology. Abstracting your problem by function also allows designers to use function databases (such as [31]) that present alternatives means of performing a desired function by way of concrete examples. 2.2.3 Assisted metaphor generation More specifically related to metaphors, several others have approached supporting and analyzing metaphors using computing tools. Most tools, however, focus on enhancing the linguistic analysis of metaphor and are less suited to use as a design tool. Martin [32] developed an approach called MIDAS (Metaphor Interpretation, Denotation and Acquisition System). His approach included the idea to transfer information from the understanding of metaphors to generation. With the input of existing metaphors MIDAS can generate new metaphors. Jones tried to come up with a transparently-motivated metaphor generator. The scope of his work was limited to a subset of verb phrase metaphors. The algorithm as designed to return a metaphor in a complete sentence, with a complete sentence as an input. The algorithm, Quipper decided if a metaphor was present and tried to formulate one that fit the input [33]. A more complete software program, though dated, is NETMET, developed by Steinhart [34-36]. NETMET is a program for generating and interpreting metaphors. However, NETMET is only able to understand specific pre-coded targetsource metaphors and their implications. With this knowledge, rather than creating entirely new metaphor possibilities, it is able to recombine existing metaphors. More recently, Veale [37], drew from a large number of similes from text on the web then used that information to generate new ones. Their case-based approach is generated from Google simile results and contains 12 thousand similes employing 4 thousand nouns with 2600 adjectival properties. Veale’s work is the closest in intent to our own and has the advantage of drawing from existing data to make new connections. Their tool ranks the strength of alternative similes based on how often connected adjectives appear on the web. 3

THE TOOL: META4ACLE This paper presents the initial development and evaluation of the Metaphor Exploration Tool Approach for Design: Meta4acle. In this section we discuss the design of the user interaction with the tool as envisaged in a final implementation

(3.2). In the prototype built in this study, the non-essential elements of the Concept Net and the Shift Board were not implemented. After describing the user interaction we present the computation performed by the prototype version of the tool as well as scalable plans for a full implementation (3.3). 3.1

Overview of the metaphor design tool We aimed to develop a tool that is simple to use, fits into a teamwork environment, and outperforms existing tools. Figure 1 displays the three primary steps of using Meta4acle. Define Objective Domain Key association : User

Search Find distant domains Find similar key associations

Results Sources Reasoning

: Computer Figure 1. The tool approach

In the first phase, the design team defines the domain of their target concept and the key associations they require of a metaphor. The second phase, performed by the tool, searches concepts in distant domains to the target and returns possible source concepts with similar key associations. In the final step, the design team has to review the suggested sources and make their own connections for how the suggestions are useful metaphors. In the final version of the tool the Concept Net will help users review and refine initial results, and the Shift Board will facilitate making meaningful connections with the results. 3.2

The interaction design Our tool has three user inputs, which are different from each other in the content and type of knowledge required of the user; some inputs need explicit knowledge and others are designed to elicit implicit knowledge. The first input is required to inform Meta4acle about the design situation and the desired characteristics of the metaphor. The second requires the users to filter the initial results, both removing obvious poor choices and refining the selection. The final step involves a manipulation of possible metaphors until a suitable metaphor is found. Below we will discuss each of these in more detail. 3.2.1 Project definition The first user input takes place in the definition phase, where the user contributes the project name and key associations of the design task. Explicit customer knowledge of this information is required to use the Meta4acle. For example, a design team may have the task of developing an improved shower experience, yet in the early phases they have no clear idea of the attributes and needs their new product must fulfill. Only after the team has performed their initial research to understand the needs and desired experience will they have the key associations with which to begin their search for a metaphor. Once they have gathered this information – for

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example, the shower must be efficient, fast, stimulating and professional – they are ready to begin. In addition to this required information, other options are available to add more information: Story or descriptive text In the early phases of a design project it can be easier to describe what the new product should do, or how the designer feels or thinks about it than explicit requirements. Areas for free-form text from project documents or interview transcripts are available which are parsed by the tool. Target domain Users can specify manually the domain, or domains, their project belongs to. In the final version this can be chosen automatically by the tool through the frequency of concepts from different domains present in the project definition text. Exclude or specify source domains The domains which the tool will search may be limited manually. 3.2.2 The Concept Net In this stage initial metaphor sources suggested by Meta4acle are refined by leveraging implicit knowledge and gut feel from the users to ‘vote up’ promising sources or ‘vote down’ poor ones. For example, ‘voting down’ a metaphor updates the initial rating of key associations as input for the computation. An analogy we use to think about this stage is Pandora for metaphors (Pandora is a popular music website that takes simple binary ratings of songs to improve an ongoing playlist [38]). Designers interact with the metaphor sources through the Concept Net. The Concept Net is a visualization of suggested metaphors as floating concepts organized in ‘clouds’ by their domains (compare Figure 2). The clouds are arranged by their conceptual distance from each other and the degree of shared concepts. Within each cloud the concepts are structured by their similar (or opposite) key associations.

from homonyms. As users provide their input the tool actively updates its suggestions by refreshing the screen. 3.2.3 The Shift Board The last user input takes place on the Shift Board, once they are presented with concrete metaphor source possibilities. The Shift Board is Magnetic Poetry for metaphors. Magnetic Poetry provides small magnetic words that can be rearranged on a fridge door, combining them to produce sentences and phrases. On the Shift Board, three different kinds of words are present: Target words e.g. Shower, Washing, Bathrooms Mapping words e.g. Is A, Is, Are Source words e.g. Reset, Cultivating, Hideouts Each class of words is a different color and they can all be moved around on the screen. On the original screen words are sorted by class with Targets on the left, mapping words in the center and Source words on the right. The sources are sorted from top to bottom by domain, concept, and similar key associations. Users are prompted to select their most promising terms and combine them with the suggested terms for the project name. This step is supported by fill words offered by Meta4acle to help make understandable sentences. Users are able to add and edit the suggestions for sources, target and mapping words to provide maximum flexibility. The final version of the tool will expand the set of words for both the target and the suggested source domains by e.g. using WordNet [39] to find semantically related words. After rearranging the terms to form coherent metaphor sentences, users can add the rationale for each choice in a text field. For non-obvious metaphors it is valuable to capture the rationale of the choice to help communicate the metaphors to others. Results from the movement of the Shift Board and final rationale are easily exported to common applications and formatted large for printing to allow discussion to continue as a team with physical artifacts (compare Figure 3). desks are a f avorite song

photo album I don’t like it! □ Domain: books □ Key

ants nest hobby

zoo

cubicle is like kids tv Similar association work is a hobby □ work □ comf ortable of f ice is a ants nest □ f ocused □ home

association

teddy bear cave

⌧ memories □ work □ comfortable

Figure 2. The Concept Net This stage also serves to improve the results by allowing them to remove obvious errors in suggestion through the tool’s misinterpretation of common language, resulting, for example,

Figure 3. The Shift Board (in the final step) 3.3

Computational model In this section we present the computational models that enable the Meta4acle to suggest metaphor sources based on user input. The information flow of the application is shown in Figure 4.

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3.3.1 Input analysis The input analysis identifies the target domain of the project from the project name and project definition text. In the prototype model the target domain is selected explicitly by the user. The input analysis also parses and interprets the free input fields for key associations. 3.3.2 Linguistic model The linguistic content of the model is divided into three main parts: the Domain Ontology; Concept Clouds associated with domains; Concept Characterization by key association. User

Tool

Launch Meta4acle Def inition of new metaphor Input analysis Concepts selected by domains and key associations Display of concept net structured by domains and key associations Net manipulation Update concept net no

User likes it?

yes

Search f or spectrum of terms f or concepts Displays of terms on shif t board

Shif t terms to create metaphors Add new words no

User likes it?

yes

Export or print f inal metaphors

Employ new metaphors on user’s objective

Figure 4. Overview of the tool process

The Domain Ontology in the prototype consists of three domains and 17 sub-domains, all classified by distance to the other sub-domains. A domain is a cloud of semantically related concepts. For example, top-level domains included Nature, Work and Transport, with some sub-domains in the Nature domain being Plants, Habitat, Natural Forces, Geography, and Weather. Sub-domains were also evaluated against each other sub-domain by a subjective measure of distance – how far, conceptually, are the domains from each other. We used a simple three level scale of short, medium and far. For example, Weekend to Weather is short, and Game to Plants is far. The concept distance is analogous to the classic logistics distance map – The triangular matrix shows distances, times and costs for routes for traveling from each city to the others. Unfortunately, we found no preexisting domain ontology suitable for use in Meta4acle so we developed a limited subset for prototyping. Existing ontologies [40] are more descriptive of language than concepts, which makes those ontologies hard to use as a basis for a design tool. The Concept Clouds are lists of concepts related to each subdomain. We developed the clouds by using Google Sets [41]. Provided with a small number of related seed concepts, Google Sets generates a list of related concepts derived from their related appearance on the web. Using this method we were rapidly able to develop a database of 448 concepts each associated with a sub-domain. Other tools are also available such as TextRunner Search [42] and the dmoz Open Directory Project [43] to achieve similar results. While for the prototype we developed our own concept cloud database structured by key associations and domain relations, for future implementation we are also evaluating using an algorithm that builds the results for the search based on a recent crawl of current web content that extracts semantic links between words. The Concept Characterization, was a by-hand ranking of each of the 448 concepts of their association with 42 adjectives. For the prototype the researchers and a small team of strong English speakers provided each rating between 0 and 10. In cases where we had multiple characterizations for each concept the ratings were averaged. The list of 42 adjectives was itself derived from the adjectives of the most used 2000 words list in English language [44]. The list included, for example, fast, quiet, cultural, natural, powerful, and light. When design teams have provided the information about their project (compare Figure A1) and launched the calculation macro; Meta4acle performs the following steps. First the distance of the target source concept to other domains is evaluated. Second, the utility value is calculated by the input adjectives and the characterized concepts, which are used to prioritize a pivot table. Third, the results are pulled by the output mask. In addition to displaying the 10 strongest metaphor source suggestions, the tool displays their domains,

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sub-domains and, when selected, the strongest key association matches between the target and source to help users understand the suggestions (compare Figure A2).

projects at the University of California at Berkeley for their use of metaphors that informed the direction of the teams [48]. By using the data from the early stages of the projects as input for the tool, we were able to seek out metaphors and then compare these metaphors to those that the teams themselves employed in their projects. The design projects were thirteen weeks in length from an initial project proposal, through needfinding, project definition, concept generation, testing and selection to a user-tested prototype at an end of semester tradeshow. Hey et al. [49] found that metaphors in these projects were used primarily in the earlier problem framing stages of the project rather than for generating new design concepts. We randomly selected three of the eight projects that employed metaphor and used the projects’ mission statements and user needs as input information for Meta4acle. We tried to simulate the time a design team may spend using the tool allowing around ten minutes for the definition phase and 20 minutes for the discussion phase. The discussion phase includes interpreting the suggested metaphors and their implications for the product and its communication. Information about each case study is presented in Table 1 including, the team’s mission statement, primary user needs, domain and sub-domain of target, strongest key associations, the metaphors suggested by the design tool and the metaphor used by the design team. Below we discuss the general direction for each team and the fit between both metaphors suggested by the tool and used by the design team during the project.

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IMPLEMENTATION AND EVALUATION To test the metaphor seeking tool we built a prototype in Excel with the essential functionality. While the interface requires refinement, a prototype at this level allowed us to evaluate the value the tool could provide, an evaluation of the method and also feedback and insights about the interface and its use by designers. The prototype allowed design teams to: 1. Input information about their project 2. Rate the key associations of their desired metaphor 3. View the 10 strongest metaphor matches and the key associations that led to their selection With the basic tool functionality we performed several early design iterations with graduate engineering design students allowing us to improve the interaction with the tool and gain an early appreciation of the tool’s value. We then tested the improved prototype on several design case studies, projects that themselves had employed metaphor. Screenshots of the tool are provided in the Appendix. In this section we discuss the context and outcome of the case studies. 4.1

Case studies To evaluate the tool we followed a similar approach to prior researchers (for example, [45], [46] and [47]) choosing to test the tool’s performance retrospectively on design cases. In prior work, we had coded graduate student product design

Table 1. Overview of case studies Domain and subdomain

Key associations for the solution

Design team selected metaphor

Metaphors found through the tool

NASCAR drive-through

Nut Flashlight Climate Rose

Name

Mission statement

Case study I – Drive Through Fast Food

Develop a modern and efficient drive through packaging. The user experiences the process of packaging.

Freetimeinterests

cheap, complementary, fast, fresh, light, modern

Case study II – CAD cost

Offer accurate cost estimation software aiding decision making throughout the plastic injection molding design process.

Worktask

active, complementary, easy, Spellchecker modern, professional, technical

Cheap flights Birds Voltage meter

Case study III – Readers Revisited

To create software that gives college students an easy, affordable, and customizeable way to consume the print content associated with their classes.

Workpurpose

active, easy, free, simple, modern, open, permanent, cheap, personal, together, complete, synergetic, light

Ecosystem Dancing

4.1.1 Case study I: Drive Through Fast Food This team set out to develop modern and efficient packaging for drive-through "fast" food service. The closest domain match was deemed Free-time and the user needs led to

Restaurant

the strongest key associations including cheap, complementary, fast, fresh, light, modern.

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During the project the team had suggested a pit-stop metaphor of the NASCAR6 Drive-Through. This metaphor draws attention to speed, quality, professionalism and safety. The design metaphor tool’s most promising metaphors included, Drive Through Packaging Is: A Nut: A Flashlight: A Climate:

A Rose:

Packaging that is contained, natural, secure, cheap and disposable Should fit with the car as well as a flashlight fits into the glove compartment Packaging that provides a protective climate for your food – keeping flavor and odors in, and protecting it from cooling and contamination Packaging suitable for a gift that is attractive, biodegradable, fresh, modular and easily fits anywhere

Critic of metaphor comparison Each of the suggested metaphors were, at first, somewhat surprising. We believe this is because the metaphors were drawn from domains distant to the target concept of drive through packaging. In contrast, the team’s metaphor of the NASCAR Drive-Through was drawn from a similar domain to the original – it involves cars, stopping, services and leaving. In this respect, though it fairly closely matches the desired attributes of a metaphor it only held potential for a minor reframing of the design situation. Further, we see that the NASCAR metaphor only focuses on a few of the primary user needs, speed in particular. It is interesting to note that one of their goals was to get away from the negative connotations of "fast food", which their metaphor reinforced to some extant. The metaphors suggested by the design tool highlight more interesting and different aspects of a possible solution than the metaphor from the related domain. 4.1.2 Case study II: CAD cost This team set out to offer accurate real-time cost estimation software to aid decision-making throughout the plastic injection molding design process. The closest domain match was deemed Work, and the user needs led to the strongest key associations of active, complementary, easy, modern, professional, technical. During the project the team had suggested a metaphor of A Spellchecker for Cost in CAD. The design metaphor tool’s most promising metaphors included, The Software Is: Cheap flights:

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A Bird:

Always have to be aware of what they can do and what the cost is to them, continually adapting to changes A Voltage Meter: A voltage needle meter that provides continuous, reactive and precise updates on cost for the part Critic of metaphor comparison All suggested metaphors were from unexpected sources and yet they quickly present a relevant and interesting new framing of the situation. What’s more, in comparison to the spellchecker metaphor, the cheap flights metaphor inspires many new relevant features for the software. Once again, the team selected a metaphor that was, conceptually, only a short distance from their target domain; spellcheckers are still software. In fact, team discussions revealed that they were somewhat unhappy with this metaphor and felt that it was limiting them to checking and estimating and not design options. The presentation of metaphors from distant domains provided surprising and interesting possibilities increasing the chances for a creative alternative view of the situation. 4.1.3 Case study III: Readers Revisited This team set out to create software that gives college students an easy, affordable, and customizable way to consume the printed content associated with their classes. The closest domain match was deemed Work, and the user needs led to the strongest key associations of active, cheap, complete, easy, free, light, modern, open, permanent, personal, simple, synergetic and together. During the project the team had developed a metaphor based around the concept of a restaurant. The RESTAURANT METAPHOR modeled a situation where the chefs are the Professors, the students are the customers and the food is the content that is served up by the Professors to the students who consumed it. Their metaphor fits well with the well documented Ideas Are Food metaphor [50] [51]. The design metaphor tool’s most promising metaphors included, The Software Is: An Ecosystem:

Dancing:

Expedia for CADCAM – their software could clearly present all the cost implications of different design decisions

Educational material is more akin to planting something yourself which grows together with others, strengthening, reinforcing and competing within an ecosystem. The vegetation in turn nourishes the cultivator Educational material is interactive, shared experience – dancing skill is displayed to others as visible knowledge. Just as knowledge is gained from others’ notes on a text, dancers learn from watching others perform and interpret new dances

NASCAR is an American motorsports association – fast cars, round a

track.

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Critic of metaphor comparison This team drew upon their RESTAURANT METAPHOR to inform their final product greater than the other two teams. Their metaphor served them well during the project, providing the team with a useful framework to make sense of the higher education system. However, during their final presentation, judges familiar with good pedagogy commented that "consuming knowledge from teachers" was frowned upon in the education community which favors constructivist approaches to learning. The design metaphor tool presented several interesting alternative ways of viewing the design situation in a way that was in concert with modern learning scienes. Perhaps the most important contribution of the new metaphors is that, rather than provide a way of viewing the current situation, as the RESTAURANT METAPHOR does, the metaphors are for the desired reality to be produced through their solution. In this respect, both the Ecosystem and Dancing metaphors hint at ways to improve the current situation thereby having the potential to serve more usefully as design inspiration. The new metaphors also have the benefit of suggesting a distinct and unique (differentiating) vocabulary with which to stimulate ideas and communicate their product. It is interesting to note that ‘Restaurant’ was suggested by the tool at position 1407. This suggests that the metaphor is indeed useful, yet it less accurately reflects all of the desired attributes of a solution. 4.2

Discussion Our experience testing Meta4acle on existing design cases revealed many benefits of the tool in practice. Convenience and simplicity ~ The short time that was needed to perform the evaluation attests to the convenience and simplicity of the tool – minimal input effort and a simple output to interpret. Productive discussion ~ Regardless of whether metaphors are ultimately adopted by the design team we observed the suggested metaphor sources quickly lead to productive discussion about the direction and benefits of the new product. The metaphor suggestions rapidly provided alternative ways of understanding the design situation. Distant metaphors, in particular, helped with a reframing of the situation – providing a different point of view. When performed as a team the act of rating the key associations of a desired solution also quickly generated productive disagreement and discussion about the nuances in the goals of the project. In this respect, the search for a metaphor through using the tool was a useful activity to help the team get on the same page as each other. Lighting the way rather than the surroundings ~ As we saw with the Readers Revisited case study, the metaphors

suggested by the tool had the added benefit of pointing out a desired direction rather than only illuminating the current reality. This helps show the design team directions to move forward with the project. Creative associations ~ By providing metaphor sources from distant domains it increased the chance of creative and surprising associations. This could be seen in the first two case studies where the metaphors chosen by the teams were from the same domain as their product. By forcing these creative associations using the tool may help reduce the incubation period that is often otherwise required to distance yourself sufficiently from the project to make a creative association. The metaphors also helped inspire interesting solution directions consistent with the desired outcome and user needs. Lowering the barrier, raising the probability ~ Many creativity techniques acknowledge the value of metaphor and provide prompts to help teams find suitable metaphors. Similarly, experienced designers are also more reliably inspired with compelling metaphors and analogies than novices. We hope with this tool that we can lower the barriers and investment required to find a useful metaphor. It is encouraging that Meta4acle is useful with only a minimal dataset. A more complete dataset may be able to match or even exceed the performance of an expert. As a greater concept base is added to the tool we anticipate the need will increase for the Concept Net and Shift Board as additional filtering stages. A team activity ~ In our early studies and when using the tool for the case studies we observed that the multiple perspectives provided by team use of Meta4acle significantly helped with both the framing of the situation and the interpretation of the suggestions. This observation reinforces the goal of developing a tool that can be used as part of a team activity. 4.3

Limitations It is clear that our evaluation is not conclusive, falling short of an evaluation through extended use by design teams in industry. We appreciate that using past cases as validation does not guarantee success within a real project situation. It is also true that as researchers on the tool we are subject to an increased willingness to find useful results from the tool where design teams may have moved on. However, applying a new tool to existing case studies has been used as an accepted early evaluation approach by design researchers. Well documented case studies of metaphor use in industry, including detailed context of the projects are few so the decision to use cases from student design projects provides an acceptable alternative. Finally, the results from each of the three case studies were positive, increasing confidence in our early conclusions.

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The tool prioritizes metaphor suggestions in a list. Ranking `Restaurant` on position 140 expresses the tool’s evaluation that 139 better metaphors were found.

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5

CONCLUSIONS AND FUTURE WORK In this paper we have presented Meta4acle, a Metaphor Exploration Tool for Design that has shown itself capable of providing metaphors as effective or better than metaphors used by teams of design students in real projects. By transforming a search for a compelling and useful metaphor from stumbling on to seeking out we have shown potential to lower the barrier for designers in terms of experience and effort required to use metaphor effectively. Although the initial evaluation is positive we are currently further developing the tool, enhancing both the interface and the database of concepts, to allow a more controlled test during a design project. Meta4acle is being redeveloped as a webbased interface to allow easy access and the benefit of improving its performance through repeated use. In order to go beyond the retrospective studies, future evaluations will be performed on student product development teams during the design process. The development of the tool has led to many potential avenues for research to better understand metaphor use in design. Questions raised include: What key associations are necessary for describing the majority of design metaphors? Are some associations more useful for design than others? What are the characteristics of concepts that consistently make good design metaphors? How does more explicit consideration of design metaphors benefit teamwork? How does the usage of the tool improve general communication skills using metaphors? The development of Meta4acle opens the door to investigating these kinds of questions. ACKNOWLEDGMENTS The authors would like to acknowledge the University of Technology RWTH Aachen – UC Berkeley Exchange Program and the support provided by the National Inventors and Innovators Alliance and National Science Foundation grants: CMMI-0555851 and DUE-0428935. We would also like to acknowledge participants and teaching staff, Sara Beckman and Leslie Speer, of the UC Berkeley New Product Development class who helped inform and inspire this research. REFERENCES [1] Norman, D. A., 1988, The Design of Everyday Things, Doubleday, New York. [2] Hertzfeld, A., 1981, The Original Macintosh, Folklore.org, Available via: http://www.folklore.org/StoryView.py?project= Macintosh&story=Bicycle.txt [accessed January 22, 2008]. [3] Cooper, A., 1995, "The Myth of Metaphor," Visual Basic Programmer's Journal. [4] Schön, D. A., 1993, Generative Metaphor: A Perspective on Problem-Setting in Social Policy, in Metaphor and Thought A. Grtony, eds., Cambridge University Press, Cambridge, UK, pp. 138-163. [5] Saffer, D., 2005, "The Role of Metaphor in Interaction Design," Carnegie Mellon University, Pittsburgh, PA, USA.

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ANNEX A: SCREENSHOTS OF META4ACLE

Figure A1. Meta4acle – the Input Mask

Figure A2. Meta4acle – the Output Mask

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