Which Metaphor for Which Database? - Semantic Scholar

Which Metaphor for Which Database? Tiziana Catarci*, Maria F. Costabile° & Maristella Matera° *Dipartimento di Informatica e Sistemistica, Universita' di Roma "La Sapienza", Via Salaria 113, 00198 Roma - Italy Tel./Fax: +39-6-49918331 EMail: [email protected]

°Dipartimento di Informatica, Universita' di Bari, Via Orabona 4, 70126 Bari - Italy Tel./Fax: +39-80-5443300 EMail: [email protected] - [email protected] The role of the users and their needs are now recognized in the database community. Many efforts are devoted to improve the quality of the interaction between the user and the database. For designing better interfaces that make the systems more usable, the use of suitable metaphors is crucial. The problem we address in this paper is whether an appropriate notion of metaphor can be tailored to the database interaction, so reflecting the peculiarities and needs of this specific field. Our argument originates from a recently published paper that presents a formalism whose aim is to provide a framework for flexible use, definition, and evaluation of visual metaphors in the specific case of database schemata. By discussing such a paper, we try to clarify concepts such as metaphor, data model, visual representation, etc. We also highlight some peculiarities of the database interaction. The considerations presented in this paper should constitute a basis towards a formal approach to metaphorical design for database interaction. Keywords: Metaphor, database, human-computer interaction, visual representations.

1 Introduction The need of a better human-computer interaction (HCI) has been widely recognized and discussed. It is generally accepted that the quality of the interaction mainly depends on the

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T Catarci, M F Costabile & M Matera

interface characteristics. Thus, the crucial point is to realize good interfaces, where the word 'good' is to be interpreted from the user's point of view. At this aim the use of a suitable metaphor is crucial. Unfortunately, speaking about metaphors in HCI is, to use a metaphor, similar to walk on a slippery floor. Indeed, neither an agreed definition of metaphor exists. The one on which most of the consensus seems to concentrate was proposed by Lakoff and Johnson: "metaphor is a rhetoric figure, whose essence is understanding and experiencing one kind of thing in terms of another" (Lakoff & Johnson, 1980). However, this is a general (and generic) definition. We would like to produce a definition of metaphor that, still reflecting the above characteristics, is specific to the particular needs of the database area, and, of course, the database users. First of all, it is necessary to clearly understand and define such needs. Looking at the literature we can find, among others, a very recent paper on metaphors and databases: "Foundations of Visual Metaphors for Schema Display" (Haber et al., 1994). The title of the paper is very appealing, and also the scientific content seems to be very good. The visual metaphor is defined as a mapping between a data model and a visual model. We argue that this definition does not reflect the basic property of the metaphor as reported by Lakoff and Johnson and other authors (Martin, 1990; Cornell Way, 1991; Carroll et al., 1988), i.e. to exploit the user knowledge of a certain realm for introducing another. Rather, this mapping formalizes the link existing between data models and visual representations as introduced in (Batini et al., 1993) and (Catarci et al., 1993). A database is typically defined in terms of a data model, but the abstract concepts of such a model need to be expressed through a representation in order to be perceived by a user. Any representation of a model aims at stressing some basic features of the model itself, and obviously a many-to-many correspondence exists between data models and representations (visual or not). Thus, a precise definition of metaphor in the database area is still lacking. We do not aim to provide one in this paper. Rather, we would like to point out the problem and figure out how the peculiarities of the database interaction are reflected in an appropriate notion of metaphor. The paper is organized as follows. In Section 2 we recall the basic definitions and usage of the metaphor in different areas, namely linguistics and HCI. Section 3 deals with the database area, starting from a short discussion of the approach presented in (Haber et al., 1994), in order to present a clear distinction among the concepts of data model, metaphor, visual representation, and drawing. It also points out the needs of the database interaction. Section 4 shows examples of metaphors exploited in the processes of query formulation and result visualization. Finally, conclusions are drawn in Section 5.

Which Metaphor for Which Database?

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2 Metaphor Origin and Use While metaphor has always fascinated linguists, philosophers and all researchers in natural language processing, only in the recent decades has metaphor been studied as an important component of language. Recent research has shown the pervasive nature of the metaphor in everyday speech. Cornell Way points out that all sections of today's newspapers abound with metaphors (Cornell Way, 1991). A typical expression in a financial newspaper could be "the economy may stall or surge ahead depending upon the financial waters it must navigate", i.e. four different metaphors are used in a short sentence. Lakoff and Johnson, in their book "Metaphor we live by", provide numerous examples to show how fundamental are metaphors in our culture and language. We adopt their definition of metaphor, which says that a "metaphor is a rhetoric figure, whose essence is understanding and experiencing one kind of thing in terms of another" (Lakoff & Johnson, 1980). Therefore, thanks to the metaphor we can move from familiar concepts to unknown ones, thus incorporating new knowledge in old . Several authors agree that metaphors consist of two sets of component concepts, a target component and a source component (Martin, 1990). The target consists of the concepts the words are actually referring to (also said the original idea). The source refers to the concepts in terms of which the intended target concepts are being viewed (the borrowed idea). Conventional metaphors are represented as sets of associations, or relations, between source and target concepts. Source and target concepts usually belong to different domains, and the familiarity with the source domain is exploited to understand the target concepts. The metaphor specifies how the source concepts reflected in the surface language correspond to the various target concepts. It establishes an isomorphism between the target and source domains. In the metaphor 'I am in Word' (Word is a document editor), the target concepts represent the state of currently using a computer process. The source concepts are those that involve the state of being contained within some enclosure. In this case, the metaphor consists of component associations specifying that the state of being enclosed represents the idea of currently using the editor. The user plays the role of the enclosed thing and the Word process plays the role of the enclosure. The literal meaning of metaphor (from the Greek word 'metaphorein') is to transfer or to carry across. It is worth noting that one of the most important aspects of metaphor is that it gives the possibility of going from familiar concepts to unknown ones. In this way, it is a medium

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for enriching our knowledge. Anyone introducing a new concept tries to present it in relation to a well known one, so simplifying the learning process. For example, the model of the atom is usually presented with reference to the structure of the solar system. This basic feature of the metaphor has been recently exploited in designing interfaces for information systems (Carroll et al., 1988). In (Mountford, 1990) the author suggests that the metaphor is a fundamental tool in creative interface design, since it provides the user with a friendlier environment to work with. Indeed, the success of the Macintosh computer interface depends on the various metaphors used. On the other hand, suggestions for easier-to-use interfaces can be obtained by observing how people perform their tasks. For example, the way the user works when sitting at the desk (writing some memos on a sheet of paper, drawing a map on another piece of paper, etc.) has led to an improvement of the interaction with the computer through the so-called plain-paper metaphor. This metaphor allows the user to work on the computer screen like on a piece of paper, i. e. jumping from a word processor to a graphic editor, and so on. Therefore, the metaphor has two complementary uses in interface design: it helps the user in his interaction with the machine, and suggests to the designer new solutions. In recent years, several visual languages and visual interfaces have been proposed, which use icons as visual metaphors for representing objects and processes on the computer screen (Levialdi, 1994). A simple example is the folder icon of the Macintosh interface, which is part of the desktop metaphor. In such an icon we distinguish the physical appearance (the picture as we see it) and the meaning assigned to that picture. The meaning is what the designer wants to communicate through the icon. The more the metaphor is appropriate and visually impressive, the easier for the user is to grasp and remember the intended meaning. On the other hand, we must be very careful in using metaphors, since they are the media through which the user forms both his or her model of the system and the expectations on the system functionalities. As a consequence, the user could be disoriented and discouraged by the failure to meet his or her expectations. The behavior of the trash icon in the Macintosh interface, when it is used to eject a disk, is an example of inconsistency. Another example comes from the use of the book metaphor in some HyperCard stacks: the action 'go to a next page' is represented by a dissolving effect of the current page, instead of using a visual effect showing that the page is being turned (Erickson, 1990). It is well known that an ideal metaphor does not exist, but it is extremely important to choose the metaphor which is appropriate depending on the particular situation. Unfortunately, there


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are not general criteria for selecting a metaphor, and it is even difficult to determine what a good metaphor is, i.e. to quantify its 'effectiveness'. A good metaphor could be one having high clarity, due, for example, to a one-to-one correspondence between the source domain and the target domain; or one being both expressive and explanatory; or one richer of details thus improving the metaphorical power; etc. Three lines of investigation on metaphor effectiveness have been suggested in (Carroll et al., 1988). The first one, called operational analysis, tries to quantize behavioral effects of using metaphoric presentations. It is based on the observation that a new complex system may be better understood (in terms of both its goals and commands) when described through other known previous systems which have some analogies with the new one. For example, programming concepts are easier to learn if introduced via concrete metaphors, like a ticket window for input, a file cabinet for storage, etc. Unfortunately, this analysis is not constructive since it provides no rules for building correct metaphors. The second research line, called structural analysis, studies the representation of mappings between source and target domains: in this way some constraints are imposed on what can and what cannot be a metaphor. The third line, called pragmatic analysis, tries to explain why some metaphor mappings are constrained by context and goals; this problem may become more severe since both context and goal could change in time unexpectedly. These three lines are complementary since they help each other in understanding and obtaining good metaphors for improving HCI. Some insights on metaphorical design are given in (Marcus, 1994; Madsen, 1994).

3 Visual Metaphors for Databases In the previous section, we have described the meaning and usage of metaphor in fields such as linguistics and HCI. The problem we want to address in this paper is whether an appropriate notion of metaphor can be tailored to the database interaction, so reflecting the peculiarities and needs of this specific field. A formal approach to the construction of effective metaphors for interacting with databases would be desirable.

3.1 Visual Metaphors for Schema Display Recently a paper has been published with an appealing title: "Foundations of Visual Metaphors for Schema Display" (Haber et al., 1994). It presents a nice formalism whose aim is to provide a framework for flexible use, definition, and evaluation of visual metaphors in the case of database schemata, but also applicable to similar structured information. The visual metaphor is seen as a transformation between abstract and visual information. In that case, the abstract information is the database schema. Therefore, the main elements of the

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formalisms are: 1) a data model that captures schemata, 2) a visual model that captures visualizations, and 3) a visual metaphor that is a mapping between data and visual models. In our opinion, the visual metaphor, seen as a mapping between a data model and a visual model, does not reflect the basic property of the metaphor, as defined by Lakoff and Johnson, and used in the everyday language and in several effective interfaces for computer systems. Haber et al. use the term metaphor with a restricted meaning, not capturing the very essence of the metaphor. Nevertheless, their formalism is valuable, since it precisely defines a mapping between visual models and data models, with many interesting properties. For instance, they formalize the concept of correctness of the visual metaphors (no valid visual schema will map to an invalid data schema and vice versa) through a relationship between the constraints in the data model and those in the visual model. The authors take a simple approach and consider straightforward subsumption conditions on group of concepts. However, they alert the reader about the intrinsic complexity of the problem of checking all the derived constraints. This problem is in itself very interesting from a computational point of view and deserves some more investigation. What we argue is that calling the above mapping 'visual metaphor' is misleading, because it does not emphasize the mapping between the source domain and the target domain, that allows exploiting the familiarity of concepts in the source domain in order to understand concepts of the target domain. Since the metaphor we are talking about is visual, there is a strict relation between the appearance of the concepts (taken from the source domain) on the screen and their meaning in the target domain. The appearance depends on elements of the chosen visual model, and the meaning refers to elements of the data model. Therefore, the relation existing between elements of the visual model G and elements of the data model D can be expressed as the mapping T: G -> D. Such a mapping is called visual metaphor in (Haber et al., 1994). However, in order for the metaphor to be effective, its source domain must be familiar to the user, typically, this is not the case of a data model domain. As a consequence, the data model should be the target domain (as defined in section 2), a familiar source domain should be chosen, and a metaphor should be defined as a mapping between the source domain SD and the data model D, i.e. M: SD -> D. Once this first mapping has been defined, what we still need is the visualization of the source domain, which can be realized by defining a mapping V between the visual model and the source domain, V: G -> SD. At this point, we can give a different definition of visual metaphor by using the M and V mappings. The former is for passing from the data model to the source domain and the second from the source domain to its visualization.


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To give an example, let us consider the well-known desktop metaphor. Using such a metaphor, the concept 'file directory' (concept of the target domain, i.e. the operating system) will be represented with the concept 'folder' of the source domain, (i.e. the office environment). Using the above notation, we can say that M(folder) = file directory. Since we are interested in visually representing such concepts, we will choose a visual model in which the folder is represented by the (now popular in several visual interfaces) folder icon, i.e. V(icon)= folder . In our opinion, compared with the mapping T defined in (Haber et al., 1994), the above definition of visual metaphor expresses more clearly the fundamental relation of the metaphor with the source domain, which helps the users learning new concepts on the basis of their correspondence to concepts in a familiar domain. It also points out that we can choose different visual models for the same metaphor. In (Haber et al., 1994) examples of mappings between visual models and data models are given. Some of them have a metaphorical power, that comes not from the mapping with the data model but from the fact that the chosen visual model has an implicit relationship with concepts more familiar to the user. For example, consider a database schema expressed in the relational model. The elements of the data model are mathematical relationships and domains. A common visualization of this data model is through tables with row and columns. The tables correspond to relationships and the columns to the attributes that indicate the role played by some domains. Such a visualization is effective because it exploits the people familiarity with the concept of tables. In this case the source model is the table and the visual model the table icon. If two slightly different visual models are used, one adopting usual tables and the other one tables with thicker borders and shadows (for aesthetic purposes only), the source domain of the metaphor is still the table. In the next section we propose a four layer structure that better clarifies the differences among metaphor, visual model, and drawing of the visual model.

3.2 Visual Metaphors in a Layered Environment It is worth noting that another important difference between the Haber et al.'s definition of metaphor and the examples listed in the previous pages is in the use of the metaphor itself. We can distinguish two types of metaphors: 1) for presenting objects, and 2) for presenting actions needed for interacting with the system. Indeed, most metaphors listed in Section 2 have been introduced for interaction purposes, i.e., in order to explain some new tasks

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through well known actions performed in familiar environment. On the contrary, the visual metaphors we spoke about in the previous section deal with the problem of representing the database content, in particular by representing the database schema through a visual model. These simple considerations lead us to point out two main problems: 1. In the database area there are at least two different needs: to let the user understand the database content and to allow the user to extract the information he or she is interested in. 2. Databases are traditionally described at two levels: an intensional level and an extensional level. These two levels exist in every data model, even if some models emphasize one of them (e.g. the extension in the relational model (Codd, 1970) and the intension in the Entity-Relationship model (Chen, 1976)). This can result, for instance, in using different metaphors for the understanding phase and for the interaction phase, as well as for the intensional level and for the extensional level. Let us start with the understanding problem. In this case the main issue is to find an effective way to transmit to the user the information content of the database. If we use Haber et al.'s definition, the scenario is such that there is a database expressed in terms of a data model, and what is exported outside is the data schema. In this case we need a four component structure in order to reach the user: • Something appealing on the screen, i.e. a drawing which renders in an artistic way what we call a visual representation. Properties of this drawing should be mainly aesthetic, i.e. the attractiveness, the clarity, the beauty1. In other words, the drawing can be seen as an instantiation of the visual representation, in that it is a way of rendering the elements of the visual model obeying to some aesthetic criteria (ticker border lines, use of shadows, etc.). • The visual representation (also called visual model in (Haber et al., 1994)), i.e., a representation which uses basic visual structures (such as diagrams, lines, icons, etc.) in order to convey a meaning to the user. Properties of the visual representation should be mainly related to the effectiveness, in the sense that characteristics of the elements of the metaphor should be reflected by properties of the visual representation. For instance, the transitivity of the relationship 'part of' can be reflected by the transitivity of the geometric property 'containment' ((Mackinlay, 1986), see also (Cruz, 1994)). • The metaphor, i.e. a mapping which exploit the user's knowledge of a familiar domain for introducing a new realm. Properties of the metaphor should be mainly related with

1

Note that what we call drawing is part of the visual model in (Haber et al., 1994).


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clarity, because a natural (from the user's point of view) correspondence between the elements to be represented (the data model constructs) and the representing elements should be generated. • The data model, i.e. a set of primitives for formally structuring the database content. Properties of the data model should be mainly related with its representational power, i.e. the richness of its constructs for structuring the information. A very simple example of this layered structure is that one where the user sees on the screen a set of circles with a border line of 1/32 inch, connected by straight lines of 1/16 inch. This is the actual drawing of a visual representation made of circles and straight lines, depicting a semantic network model through the node and arc metaphor. The advantages of using the above approach are in its high modularity and modifiability (for instance, the drawing can be a method attached to each class of visual structures). Moreover, the number of features and constraints to be checked for verifying the correctness of each component (and of the mappings among them) are highly reduced. All the above still refers to the hypothesis of presenting to the user the intensional part of the database, i.e. a data schema. Note that in this way we use a metaphor for mediating between the data model and the user, but the data model itself is a first meeting point between the reality of interest and the sequence of bits stored in the computer memory. However, the user has a certain mental model of the reality of interest, which is not necessarily reflected by the metaphor used for showing the data model. Moreover, once the user wants to see the information he or she has extracted from the database (see Section 4), he or she passes to the extensional level, and the metaphor used for the intensional level could be no longer meaningful. This can result in a change of metaphor, visual representation, and so on, but, if this is the case, the two different metaphors should be as close as possible, in order to avoid to puzzle the user. A different choice relies on avoiding the visualization of any data model. In this case we can imagine to offer to the user (we refer to the database end-user) a scenario where the information contained in the database is pictorially represented as a virtual reality, so that the user is no longer aware of a presence of a structured database, but he or she is interacting as in the real world. Although in this case there is no metaphor from the user point of view, there is still a metaphor from the designer point of view to bring out of the database (which is not the reality but an internal representation of it) the reality that was meant to be represented when constructing the database (Ioannidis, 1994). There is still the problem of establishing a correct

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mapping between this realistic representation of the information (which is not based on a data model) and the actual data (which need to be structured and codified in order to be stored). Thus, it seems that an appropriate data model still remains a good compromise between the needs of both the user and the designer. What we said above refers to the problem of letting the user understand the content of the database. This can be seen as a first phase of the interaction, preliminary to the other one, where the user extracts from the database the information of interest. The use of a metaphor can also help in this phase, and it would be desirable to choose the same metaphor adopted in the understanding phase, in order to avoid the possible user disorientation, but in principle the two phases can exploit different metaphors. Similarly to what we did for the understanding problem, we can consider a four component structure for the query problem: • The execution, i.e., the way in which the direct manipulation actions are actually performed by the user. For instance, in a system equipped with the data glove the user can grasp the objects on the screen, in a keyboard-based system the same action relies on a combination of keys. • The visual representation of the query, obtained by applying direct manipulation mechanisms on basic visual structures. • The metaphor, i.e., a mapping between the elements of a domain familiar to the user (source domain of the metaphor) and the elements of the query model. • The query model, i.e. a set of operators and rules used for expressing the queries. An example of a query model is the relational algebra, whose operators allow one to express both set-theoretic operations such as union, intersection, difference, etc., and others such as select, join, etc. Given a query in relational algebra, we may state the query in terms of several visual representations, that exploit appropriate metaphors in order to be effective (Batini et al., 1993). Another open problem is to understand whether the above modular structure is suitable for formalizing the task of visual query formulation.

4 Examples of metaphors for database interaction Haber et al. focus on metaphors for schema display and do not discuss the query problem. On the other hand, this problem is widely treated in the literature, even if from a less systematic point of view than the one we present in Section 3.2. Indeed, several systems for visually


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querying database (Visual Query Systems or VQSs) have been proposed (a survey is in (Batini et al., 1993)). Typically, such systems do not provide a rigorous approach, instead they mainly offer a visual representation of the database and some interaction mechanisms. In our recent research we tried to move towards the above mentioned 'layered' approach by defining the architecture of a so-called multiparadigmatic VQS. Such a system provides an environment for querying databases expressed in different models and an adaptive interface exploiting several visual representations and interaction mechanisms (Catarci et al., 1994; Catarci et al., 1995). The most notable features of our approach are: • The presence of a common formalism for expressing databases. This formalism is sufficiently abstract to represent, in principle, a database expressed in any of the most common data models; • The precise definition of suitable translations among different representations in terms of both database content and visual interaction mechanisms; • The construction and the management of an effective user model, which allows the system to propose to the user the most appropriate visual representation according to his or her skill and needs. Our multiparadigmatic VQS is an example of system in which the data model of the underlying database is rendered on the computer screen through different visual representations in order to fit the characteristics of the different database users and tasks. Such visual representations relay on several metaphors to be more effective in presenting to the users the reality of interest and allowing them to manipulate it. For instance, the form-based and iconic visual representations exploit different metaphors: the former refers to the tables usually employed in the office to organize data, the latter to the objects of the real world. The visual representations are displayed on the screen through appropriate drawings, which emphasize aesthetic criteria that depend also on the available hardware devices (a colour screen, a black-white screen, etc.). For more details and examples see (Catarci et al., 1995). The interaction paradigms are influenced from the visual representations. Indeed, queries on diagrammatic representations are mainly expressed by following links, form-based queries are often performed by filling forms with prototypical values, and iconic queries can be constructed by spatially composing primitive icons (Batini et al., 1991; Chang, 1990). It is therefore useful to have a single interface offering different interaction mechanisms for expressing a query, depending on both the experience of the user and the kind of the query to be formulated.

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O. Wilde

E.A. Poe

4

D. Alighieri

2

1

Figure 1: Iconic representation of the result of the query 'Find all books in the library whose authors are: E.A. Poe, O. Wilde, D. Alighieri'.

E. A. Poe O. Wilde D. Alighieri

Figure 2: The result of the same query of Figure 1 represented as a pie-chart. Visualizing the retrieved results is also very important even if quite difficult, as it is argued in (Mackinlay, 1986). Different graphical techniques have shown to be appropriate for various situations. An interface designer should consider all situations that may arise, draw up the appropriate presentations, and then decide which is the most effective for each situation. This problem has been addressed in (Chang et al., 1994), where it is presented an interface for a database that, beside offering different paradigms for query formulation, also provides different result representations, including icons, forms, pie-charts, bar-charts and virtual reality. In Figures 1-5 we illustrate the presentation of the result for the query 'Find all books in the library whose authors are: E. A. Poe, O. Wilde, D. Alighieri', according to the above different


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representations. As we can see, with the iconic, pie-chart and bar-chart representations the number of book instances for each authors is shown. With icons we simply represent the variety of instances for each object. Pie-chart and bar-chart provide users with further implicit information: the former evidentiates the proportion among the subparts of a whole; the latter allows easy comparisons between different quantities. Since the database stores the books of a library, we also represent a Virtual Library in which the physical locations of books are indicated by icons in a 3D presentation of the book stacks of the library (see Figure 4). The books constituting the query result are shown blinking and with different textures (or colours) which denote different authors. The selection of one blinking book causes the visualization of all the corresponding information (see Figure 6). Finally, the form-based paradigm shows a table containing several information, e.g. the title, the authors, and the number of pages of each book.

5 4 3 2 1

E. A. Poe

O. Wilde

D. Alighieri

Figure 3: Bar-chart representing the result of the same query of Figure 1. This representation allows easily making comparisons between different quantities.

E.A. Poe O. Wilde D. Alighieri

Figure 4: Result of the same query of Figure 1 shown in the Virtual Library. The retrieved books are shown with blinking icons of different texture (as indicated in the legend).

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The above are not all equivalent representations. In other words, they do not have the same 'representational power'. For example, a form is suited to contain different information than a pie-chart or a bar-chart. As a consequence, the system offers various alternatives to the user, who can choose how to visualize the query result, or look at same time at different result representations shown in different windows on the computer screen.

Author name

Title

N. of pages

E. A. Poe

The Gold Bug

178

E. A. Poe

The Black Cat

150

E. A. Poe

The Purloined Letter

110

E. A. Poe

The Murders in the Rue Morgue

95

O. Wilde

The Picture of Dorian Gray

60

O. Wilde D. Alighieri

The Happy Prince

150

La Divina Commedia

825

Figure 5: Form-based result representation of the same query of Figure 1. It contains detailed information about each retrieved book.

La Divina Commedia Dante Alighieri 825 pages

Figure 6: Information on a book obtained by selecting one of the blinking books of Figure 4. The layered structure for the visualization of the database content proposed in the previous section is applicable to the result visualization. The metaphor and the visual representation are two distinct components. Obviously, the metaphors used in conjunction with the various visual representations may differ. This is the case of the form-based and iconic


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representations, as discussed above. On the contrary, the same metaphor is shared by the iconic representation and the Virtual Library.

5 Conclusions This paper is mainly intended to emphasize some open problems and solicit discussions, rather than presenting well established results. Even if the role of the users and their needs are now recognized in the database community, there is still the need of a rigorous approach which clarifies and formalizes all the elements of the interaction and their roles. One of our objectives is to state an appropriate notion of metaphor for the interaction with databases. Indeed, metaphors have recently been exploited in designing interfaces for computer systems, as a tool for easier understanding the functionalities of the systems. Unfortunately, to design 'good' metaphors is a difficult task, and a formal theory would be desirable. A first contribution in this direction is in (Haber et al., 1994), where a nice formalism is presented, whose aim is to provide a framework for flexible use, definition, and evaluation of visual metaphors in the specific case of database schemata, also applicable to similar structured information. The definition given in that paper does not reflect the basic property of the metaphor, that is to exploit the user knowledge of a certain realm for introducing another one. In this paper we have tried to clarify such a property of the metaphor, and we have also highlighted some peculiarities of the database interaction that can contribute, in our opinion, to come up with an appropriate notion of metaphor for designing better interfaces for databases. Our feeling is that this can be more easily obtained through what we call a 'layered' approach, where a high modularity comes together with the possibility of a suitable formalization. Nevertheless, other proposals are welcome.

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