A Visual Retrieval Environment for Hypermedia Information Systems ppt

A Visual Retrieval Environment for
Hypermedia Information Systems
DARIO LUCARELIA and ANTONELlA ZANZI
Centro Ricerca di Automatic, ENEL
We present a graph-based object model that may be used as a uniform framework for direct
manipulation of multimedia information. After an introduction motivating tbe need for abstrac-
tion and structuring mechanisms in hypermedia systems, we introduce the data model and the
notion of perspective, a form of data abstraction that acts as a user interface to the system,
providing control over the visibility of the objects and their properties. A perspective is defined to
include an intension and an extension, The intension is defined in terms of a pattern, a subgraph
of the schema graph, and the extension is the set of pattern-matching instances. Perspectives, as
well as database schema and instances, are graph structures that can be manipulated in various
ways. The resulting uniform approach is well suited to a visual interface. A visual interface for
complex information systems provides high semantic power, thus exploiting the semantic
expressibility of the underlying data model, while maintaining ease of interaction with the
system. In this way, we reach the goal of decreasing cognitive load on the user, with the
additional advantage of always maintaining the same interaction style, We present a visual
retrieval environment that effectively combines filtering, browsing, and navigation to provide an
integrated view of the retrieval problem. Design and implementation issues are outlined for
MORE (.Multimedia Object Retrieval Environment), a prototype system relying on tbe proposed
model, The focus is on the main user interface functionalities, and actual interaction sessions are
presented including schema creation, information loading, and information retrieval.
Categories and Subject Descriptors: H.2. 1 [Database Management]: Logical
Design—data
models:
H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval-query
~ormulation; selection process; H.5. 1 [Information Interfaces and Presentation]:
Multimedia
Information Systems—hypertext nauigatiorr and maps; H,5.2 [Information Interfaces and
Presentation]: User Interfaces-interaction styles
General Terms: Design, Human Factors, Management

Additional Key Words and Phrases: Browsing, complex objects, direct object manipulation,
graph-oriented models, hypermedia applications, information filtering, visual interface
This work was supported by the Italian Electrical Energy Company under the research project
0. L.240 Multimedia Systems.
Authors’ addresses. D, Lucarella, Centro Ricerca di Automatic, ENEL, Via Volta 1, 1-20093
Cologno Monzese, Milano, Italy and Dipartimento di Scienze dell’Informazione, University
degli Studi di Milano, 1-20135 Milano, Italy; email: lucada(Q imicilea.cilea.it; A. Zanzi, Centro
Ricerca di Automatic, ENEL, Via Volta 1, 1-20093 Cologno Monzese, Milano, Italy; email:
zanzifl cra.enel.it.
Permission to make digital/hard copy of part
or all of this work for personal or classroom use is
granted without fee provided that copies are not made or distributed for profit or commercial
advantage, the copyright notice, the title of the publication, and its date appear, and notice is
given that copying is by permission of ACM, Inc. To copy otherwise, to republish, to post on
servers, or to redistribute to lists, requires prior specific permission and/or a fee.
@ 1996 ACM 0734-2047/96/0100-0003 $03.50
ACM Transactions on Information Systems, Vol. 14, No. 1, ,January 1996, Pages 3-29.
4. D. Lucarella and A. Zanzi
1, INTRODUCTION
Hypermedia has been simply defined as a system to manage a collection of
information that can be accessed nonsequentially. It consists of units of
information that are arbitrarily diverse in form and content. Such units may
contain texts, graphics, images, sound, video, and animation and are con-
nected by logical links to form an information network. The variety of nodes
and links that can be defined makes hypermedia a very flexible environment
in which information is provided both by what is stored in each node and by
the way the information nodes are linked to each other. In addition, current
hypermedia systems provide sophisticated user interface tools that enable the
reader to inspect the node content and to navigate through the network by
selecting paths to follow on the basis of interests emerging along the way

[Nielsen 1990].
There is a growing interest today in such technologies for the implementa-
tion of massive multimedia information systems, but unfortunately, several
well-recognized problems continue to be open research issues [Halasz 1988].
Among these, central points to be addressed are information modeling and
information retrieval.
1.1 Information Modeling
The simplicity of the basic hypermedia model does not appropriately repre-
sent the structure of the information. There is an inadequate separation
between a node in the hypermedia network and the content associated with
the node. Conversely, a strong separation of the structure from the content
would allow many structures to be superimposed over the same set of
information units or a unit to be shared among many nodes within a single
structure. In addition, a node is a storage unit for a collection of data items
without any structural information, and each node and link are assumed to
be of the same type. As a result, modeling is more or less a bottom-up process
in which we have to analyze how information can be broken down into
different elements and then to recognize these individual elements by adding
links among them. The problem here is that such an analysis is only useful
for that particular instance, and we cannot use this same structure for other
instances [Tompa 1989].
The key point is that the basic hypermedia data model is too simplistic. It
is not suitable for modeling the real world or capturing its semantics as
required in most applications [Furuta and Stotts 1990; Garzotto et al. 1993;
Schnase et al. 1993a]. As a consequence, the user has dif%culty in perceiv-
ing the conceptual model of the application, resulting in cognitive overhead
[Conklin 1987]. In authoring mode, extra mental effort is needed to establish
the links required to connect the created nodes. In reading mode, extra
mental effort is needed for choosing the path to follow through the network,
with the risk of becoming lost or disoriented.

One of the main ideas proposed by Garg [ 1988] is that information embed-
ded into the hypertext network should be described by a set of predefined
ACM Transactions on Information Systsms, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 5
domain objects. In this way, the actual content of the hypertext would be
represented by a set of information objects, each of which is an instance of a
domain object, inheriting by default all of the properties of the domain object.
The idea can be compared to the notion of database schema, as opposed to a
specific instance of the database. According to this trend, many hypermedia
systems have been proposed with the support of underlying databases
[Campbell and Goodman 1988; Christodoulakis et al. 1986; Lange 1990;
Schnase et al. 1993b; Schutt and Streitz 1990].
Recently, requirements for representing the structurally complex interrela-
tionships that arise in hypermedia have generated a renewed interest in
semantic data models [Hull and King 1987]. Semantic models attempt to
provide more powerful abstraction and structuring mechanisms for specifying
database schemas in order to overcome the limited modeling capabilities of
traditional database systems [Beeri 1990; Lieberherr and Xiao 1993].
Schnase et al. [ 1993a] presented a comparative analysis of semantic
models, concluding that a structural object-oriented paradigm appears to be
superior for hypermedia modeling. Of particular interest are graph-based
data models since they provide a natural way of handling data that appear in
applications such as hypermedia or multimedia information systems. Gyssens
et al. [ 1990] proposed a graph-oriented object database model in which the
database schema as well as the database instances can be seen as graphs
with the data manipulation language expressed in terms of graph transfor-
mations. Amann and Scholl [1992] presented a graph data model with an
associated algebraic language based on regular expressions over the data
types and showed how such a language can be exploited for hypertext
querying. In the same direction, in this article we propose a graph-based

object model which provides high semantic expressibility, and we use it as a
uniform framework both for conceptual modeling and for direct manipulation
of the stored objects.
1.2 Information Retrieval
In hypermedia information systems, interaction is mainly devoted to informa-
tion retrieval. A canonical approach is based on formal querying [Bertino
et al. 1992; Straube and Ozsu 1990]. Conversely, browsing techniques consist
of exhaustively viewing part of the information base until the desired infor-
mation has been found. The former approach requires a deep knowledge
about the query language, the conceptual structure of the application, and
the goals; the latter does not require a preliminary knowledge. On the other
hand, a formal query, if correctly formulated, can be directly evaluated and
may yield an immediate answer, whereas a browsing session can take a long
time before converging to the goal or may not converge at all. Between these
two mentioned interaction techniques, other approaches must be studied with
the aim of balancing expressive power and ease of use.
Some approaches to the integration of query-based retrieval strategies in a
hypertext network have been proposed recently. Logic-based languages have
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
6.
D. Lucarella and
A. Zanzi
been proposed by Consens and Mendelzon [1989], Lucarella [1990], Afrati
and Koutras [1990], and Beeri and Kornatzky [1990]; different attempts to
exploit the hypertext links in the retrieval of the relevant nodes have been
reported by Croft and Turtle [1989], Lucarella and Zanzi [1993], and Frei and
Stieger [1992]. A common aspect to such proposals is that no concept of
schema has been introduced, and thus, queries can be specified only over the
hypertext network in order to get an optimal starting point for browsing.
Conversely, as remarked in the previous section, the approach we are

taking in this work is based on a semantic data model, the primary objective
being to provide powerful visual constructs for representing a variety of
abstractions in a structured fashion. Unfortunately, as soon as the underlying
data model becomes more complex, the level of complexity of the associated
query language and the level of knowledge required by the user also increase.
The main goal becomes the design of a language that provides both high
semantic power and ease of interaction with the system.
With this objective in mind, we propose a visual query paradigm. The user
performs actions symbolically and directly on the screen and is able to
express operations by grabbing and manipulating visual representations of
objects. The user is not required to know any complex formal language, with
the advantage of maintaining the same interaction style normally used
during browsing. The effect produced by the query is perceived as a form of
filtering and navigation space restriction, So it is natural to pass from
querying to browsing and vice versa, depending on the type of user, the type
of application, and the type of current needs. By effectively combining brows-
ing and querying under a uniform interface, we provide an integrated view of
the retrieval problem.
Much research has been carried out in the database community on graphi-
cal query languages that has influenced our approach at different levels.
Basic principles and a survey of such efforts can be found in C!atarci [1992]
and Batini et al. [1992] respectively. Most graphical interfaces are based on
intensional data models, typically the entity-relationship model [Angelaccio
et al. 1990; Kuntz and Melchert 1989; Wong and Kuo 1982] or the extended
entity-relationship model [Auddino et al. 1991; Czejdo et al. 1990]. ISIS
[Goldman et al. 1985] and its extension ISIS-V [Davison and Zdonik 1986]
provide a visual interface to the semantic data model SDM [Hull and King
1987]. SNAP [Bryce and Hull 1986] is a system based on the IFO data model
[Hull and King 1987]. More recently, some projects have dealt with object-ori-
ented data models [Epstein 1990], and DBface provides a tool for building

graphical interfaces to object-oriented databases [King and Novak 1993].
The remainder of this article is organized as follows. Section 2 provides a
description of the semantic model on which the MORE system is based. This
section also includes an example subschema that contains multimedia infor-
mation about the organization and the activities of our research division. The
visual retrieval environment along with the formal definitions of perspective
and the operations on perspectives are presented in Section 3. Various
examples illustrating the expressive power of the language are presented
ACM Transactions on Information Systems, Vol. 14, No. 1, Janusry 1996
Visual Retrieval Environment for Information Systems . 7
with reference to the example subschema shown in Section 2. Section 4
sketches design issues for the MORE prototype system focusing on the main
functionalities and presenting visual interaction screendumps taken from the
actual application. Section 5 provides a comparison with related work. Fi-
nally, brief conclusions and future research work are outlined in Section 6.
2. A GRAPH-BASED OBJECT MODEL
The basis of the approach is the characterization of the information system in
terms of objects, attributes, and relationships, namely, a general object-ori-
ented conceptual model. An object is an entity of the real world, a concept, an
event, a process, or anything else that an application tries to capture and
represent. Objects have their own identity that does not change throughout
their lifetime and are known by their properties. The specific set of properties
used to describe a given object depends on the point of view and the purpose
of the modeling. We recognize properties only through attributes. Objects
having the same structural properties are grouped together to form an object
class. Classes can be related by a superclass-subclass relationship in which
an object in a subclass inherits the structural properties from its super-
classes.
Object attributes can be divided into two general categories: simple and
complex. The domain of a simple attribute is a system-defined basic type; the

domain of a complex attribute is a class.
At the intensional level, the conceptual schema captures this semantic
structure. It is defined by a collection of interrelated classes and types, and as
such it can be represented by a directed labeled graph. Objects and classes
are related by the instantiation relationship. At the extensional level, the
information system can be viewed as a collection of interrelated objects, and
as such it can also be represented by a directed labeled graph. Thus, the
information system can be represented by graphs at both the intensional and
the extensional level. A formal definition of such concepts is given next.
2.1 The Model
Definition. The conceptual schema 2 is defined as the five-tuple
where:
—C is a finite set of class names; each class c E C denotes a structure (in
terms of attributes) and an extension (the collection of objects that have
that structure).
—T is a finite set of type names (e.g., integer, text, picture) built into the
system; each t E T denotes a type of primitive object, and V(t) is the set of
associated values.
—A is a finite set of attribute names. Attributes are defined on classes.
Attributes may be simple or complex. The domain of a simple attribute is a
ACM Transactions on Information Systems, Vol. 14, No. 1. January 1996.
8.
D. Lucarella and A, Zanzi
basic type t ● T; the domain of a complex attribute is a class c e C. In
addition, we distinguish between single-valued attributes As and multival-
ued attributes A., with A = A, U Am.
—9 c C
x A x (C u T) is the property relationship. If (c,, a, Cj) =9, then
the class c, has the attribute a, having as a domain the class or type Cj.
—% c C x C is the inheritance partial ordering relationship. If (cl, c, )

●%,
then the class Ci is a subclass of the class Cj inheriting attributes from CJ.
Definition. Given X, the conceptual schema graph is a directed labeled
graph
G(Z) = (iV, E),
where:
—N = C
U T is the set of nodes. For each c = C, we have a rectangular-
shaped node labeled c. For each t E T, we have an oval-shaped node
labeled t.
—E is the set of edges. For each (c,, Cj) = % we have a bold edge connecting
Ci to CJ.For each (c,, a, c,) = @ we have an a-labeled edge from Ci to Cj.
Particularly, if a = As we have an edge with a single arrow; if a
● Am we
have an edge with a double arrow.
Definition. The multimedia information system M is defined as the four-
tuple
M=(X, O, Y, P),
where:
—2 is the conceptual schema defined above.
—O is the set of objects stored into the system.
—> c O
x C is the instantiation relationship. Each object o = O is an in-
stance of a class c = C.
—% c O
X A X (O U V(T)) is the link relationship. (o,, a, Oj) =9 denotes
that the attribute a of the object Oi has the value Oj. Assuming the o,
instance of c, and the Oj instance of c,, we have (o,, a, o,) ~& iff one of the
following conditions holde:
(1)

(Cl, U,Ci) G 9;
(2) (c,, Ck) ~ 2?A (ck, a, cj) G 9; (the conditions or alternative)
(3) (cj, c~) ~%’A (C,, a,ck) =9.
The last two conditions are the direct consequence of the semantics of the
inheritance relationship.
Definition. Given the multimedia information system M, an instance
graph is a directed labeled graph
G(M) = (N, E),
where:
—N = O
U V(T) is the set of nodes. Nodes represent objects (rectangular
nodee) or values (oval nodes) generated from the schema through the
instantiation relationship.
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 9
Fig 1, Graph-based object model: Intentional and extensional levels
—E is the set of edges. For each (o,, a, o~) = Y’, there is an a-labeled edge
from o, to 0].
Based on this model, Figure 1 gives an example that shows how we can use
a graph-based representation at both the intentional and the extensional
levels. Note the effect, at the extensional level, of the inheritance relationship
between the class student and the class person.
2.2 A Sample Hypermedia Application
In order to demonstrate the capabilities and the flexibility inherent in the
approach discussed, a hypermedia application has been developed. The appli-
cation is aimed at storing multimedia information concerning the structure of
the organization and the activities of our research division. It describes the
hierarchical structure of the research units, including information about
management, personnel, financial budget, research projects, and project lead-
ers. A portion of the schema graph is presented in Figure 2. This schema

is used throughout the article as the knowledge base to which all visual
operations will be posed.
With reference to Figure 2, rectangular nodes in the graph represent
classes, and oval nodes represent basic types. Labeled arrows starting from a
class depict the properties of that class. Multivalued properties are shown
with double-headed arrows. The bold lines express the inheritance is-u
relationship from a subclass (at the tail of the arrow) to its superclass.
In the following, we describe in further detail the meaning of the objects
depicted. Research Unit groups the common attributes (name, direction,
ACM Transactions on Information Systems, Vol. 14, No 1, ,January 1996.
10 . D. Lucarellaand A. Zanzi
1
pmonnr.1
expmses
is-a
Research direction
unit
t+
is-a
is-a
I
is-a
Division
Fig.2. Conceptualschemagraph.
mission, personnel, and expenses) shared by the units at different hierarchi-
cal levels. The Research Division represents the administrative and strategic
central headquarters to which all of the research centers spread throughout
the country report. The Research Center is a department, characterized by a
specific research area with its own laboratories. The Laboratory is the
operative research unit, with its own equipment, in which the research

projects are carried out.
The Research Project is characterized by title, subject, description of
objectives, project leader, and a short movie presenting its current state with
the main results achieved. Note that some research programs are carried out
as joint projects, and consequently, a cycle is present in the graph. The
Experimental Installation represents an installation characterized by its
name and location, where some experiments that cannot be made in the
laboratories are carried out in the field.
The Person groups the common attributes (name, resume, and photo)
shared by the manager and the project leader. The Manager is the head of a
research unit: the central division, a research center, or a research labora-
tory. The Project Leader is a person who is in charge of a research project.
Finally, the Employees class gives information about the personnel in a
research unit, grouped by category and by age, respectively; and the Budget
class represents the financial planning of a unit, both in terms of the
estimate of the expenses and of the balance.
Note that the conceptual schema of the application is directly entered and
manipulated on the screen by the application designer supported by an
appropriate visual tool (see Section 4).
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 11
3. VISUAL INFORMATION RETRIEVAL
In this section we deal only with the retrieval and presentation issues
without considering other functionalities. In addition, a clear distinction
between the information user and the information supplier is quite common
in these systems, since object loading and updating often require specialized
multimedia editors depending on the type of object manipulated.
We have already discussed in the introduction the main reasons for devel-
oping a visual interface based on the direct-manipulation paradigm and the
expected advantages for the end users in terms of abstraction power, ease of

interaction, and flexibility. Basic requirements are the visualization of the
conceptual schema as well as the database instances, by enabling the user to
filter the amount of information to be displayed. Selective information visual-
ization can be used to locate relevant information and to restrict the visual-
ization to the pertinent parts.
A reasonable way to present complex information is to produce multiple
views of the same information, each focusing on different aspects and thus
conforming to different needs. The cognitive overhead required to face tan-
gled information structures can be alleviated if the system presents only the
relevant pieces of the stored information while hiding the rest, In analogy
with the views in databases, we introduce the notion of perspective, 1 a form
of data abstraction that acts as a user interface, providing control over the
visibility of the system objects. A perspective can be tailored to focus selec-
tively on the subset of information that is significant to a particular applica-
tion. Essentially, perspectives are graph structures that are built from the
schema graph and are visually manipulated in various ways. Related works
on graph-based object manipulation are reported by Andries et al. [ 1992] and
Guo et al. [1991].
In the following, we provide formal definitions for perspectives and a basic
set of operations that can be performed on perspectives. For each of these in
turn, we give the formal definition, the visual expression, and an example
referring to the previous application.
3.1 Perspective
Defin ition. Given a multimedia information system, a perspective P is
defined as P(rr, S ),where:
— rr is the perspective pattern, that is, a weakly connected subgraph of the
schema graph 2; hence, N( rr) c N(Z) denotes the subset of schema nodes
(classes and types) included in the perspective, and E(n) g E(2) denotes
the set of edges (properties) associated with such nodes.
—S is the set of object graphs generated by the perspective graph T through

the instantiation relationship. Given an instance s E S, each node o = N(s)
1The term perspect~[x, has already been introduced by Garzotto et al. [ 1993], hut with a different
meaning.
2A directed graph is weakly connected iff the graph obtained by removing the arrowheads is
connected
ACM Transactions on Information Systems.
Vol. 14. No 1. January 1996
12 .
D. Lucarella and A. Zanzi
name
1
Person
A
is-a
I
Research
unit
Research
Center
subject
Fig. 3. A perspective over the schema.
is an instance of the corresponding node c E IV(w) and the edge ( Oi, a, Oj)
= E(s) iff the edge (ci, a,cj)
● E(m).
So, a perspective is defined by a pattern (the intensional representation) and
by the corresponding object graphs (the extensional representation).
In order to define a perspective, the user has to build the pattern into the
“perspective window.” The requested nodes are copied from the “schema
window” by pointing and clicking. The system checks automatically that the
resulting graph is connected. In this way, incorrect perspectives cannot be

specified, since the patterns conform to the structure of the schema.
In Figure 3 we show a perspective focusing on those parts of the informa-
tion system in which the user is interested. In the example, attention is
restricted to the research centers and their laboratories including, for each of
these, the research projects and corresponding project leaders.
Perspectives can be named, saved, reused, and manipulated in various
ways. In particular, it is possible to define perspectives on perspectives,
thereby producing different levels of abstraction. All of the operations on
perspectives are closed, thus removing the major drawback of current object-
oriented query languages that do not maintain the closure property [Shaw
and Zdonik 1990]. Consequently, in our approach, the result of each operation
has the same structural properties as the original objects; thus, it can be
further processed by the same set of operators.
3.2 Object Filtering
In order to restrict attention to a subset of pattern instances in the perspec-
tive, a filter can be defined over it.
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996
Visual Retrieval Environment for Information Systems . 13
CRA c>rCRIS
‘rt’ -3
Is-a
Research Project
Unit
P
Leader
string
is-a equipment
joint
in-char e
M.lumdm Swwm

projects
subject
presentation description
Fig,4. Filterspecification.
Definition. Given a perspective P(T, S), a filter F is defined in terms of a
set of selection conditions {Cl, . . . . Cn) over the pattern. Let a, be an attribute
of type t pertaining to a node (class) n, in the pattern m; then C, represents a
selection condition over the actual values of the corresponding object in-
stances. The selection condition is a boolean combination
A, v , 1 of simple
expressions of the form (al e aj ), where al is a type-compatible property or a
constant, that is, some value from the domain t; e is a comparison operator
depending on the type of the operands.
In Figure 4 a filter has been defined over the perspective shown in Figure
3, with selection conditions over two (shadowed) nodes. In particular, this
example is the visual expression of the following complex query: “I want to
know if, in the research centers named C.R. A. or C. R. 1.S., there are research
projects in the field of Multimedia Systems, and if this is the case, I want to
see the laboratories where the activities are carried out and the responsible
project leaders.”
From the user’s point of view, one merely “clicks,” one by
one, on the nodes in the pattern over which conditions have to be specified.
The clicked node changes its color (shadow in the figure), and a text window
is opened to enable the user to enter the requested conditions.
As is well known, in case of recursive properties (e.g., “joint” on “Research
Project”), a selection condition specified over the class “Research Project” or
related ones can have different semantics. We decided to allow a very limited
form of recursion in order to guarantee immediate comprehension and ease of
formulation, which has been our constant guideline in the design of this
system. So the specification of conditions either over the class “Research

Project” or over related classes yields the retrieval of projects satisfying the
ACM Transactions on Information Systems. Vol. 14. No. 1, January 1996
14 . D. Lucarella and A. Zanzi
conditions. Then the projects joined to each of them are retrieved. Namely,
the condition is intended as a starting condition for the computation of the
transitive closure. The effect of a recursive property at the extensional level is
shown in the next example.
Definition. Given a perspective P(m, S) and a filter F defined over P, a
selection operation u returns a subset R c S of pattern instances matching
the filter:
(rF(P)= R={ SISESASE F}.
A pattern instance s matches the filter iff it satisfies all of the conditions
A i. ~,. CL; a condition C, over the class i is satisfied ifl it is true for the
corresponding object instance values.
From the user’s point of view, after having specified the pattern and the
filter, it is enough to “click the “select” button. The system notifies the user,
resetting the button when (1) the query has been processed and (2) the
matching instances have been identified. In this way, it is possible to restrict
the attention to a subset of instances according to the conditions specified in
the associated filter. From now on, it will be possible to access the single
objects belonging to the retrieved set R of pattern instances or to iterate the
process by further modifying the perspective.
The impression perceived by the user is that a profile is defined denoting
the user’s interests; the system filters out useless information; and the user
sees what is left. The effect of this filtering capability is to restrict the
attention to a manageable subset of nodes. For a discussion on the features
qualifying the information retrieval and information-filtering processes, see
Belkin and Croft [1992].
In the following example, we show the effect of the selection operation at
the extensional level. Assume we have a basic perspective PI focusing on the

“Laboratory,” relative “Budget,” and “Research Project” with “Project Leader.”
In Figure 5(a), the pattern of the perspective is reported together with the
corresponding pattern instances (for simplicity, only rectangular nodes are
shown, and link names are not reported). Figure 5(b) presents the instances
retained after the definition of the perspective Pz and the execution of a
selection operation on the basis of the specified filter.
Definition. Two perspectives P1(T1, S1) and Pz(~z, Sz) are said to be
compatible when they have the same pattern but different instance sets:
Tr~= 7r2; sl # S2.
This is the case resulting from the application of different filters to the
same original perspective.
3.3 Basic Operations on Perspectives
Now we introduce basic binary operations to combine perspectives together.
Definition. Let Pl(nl, S1) and PZ(TZ, Sg ) be two perspectives, with ITl #
Vz and N(TI ) n N(T2 ) # O. A composition operation @ over the set of nodes
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 15
b)
Fig, 5. (a) Pattern and instances of perspective PI. (b) Result of the selection operation defined
on perspective P2.
N’ = N(TI ) n N(mz ) generates the perspective P(m, S) = PI @ P2 where:
— r is the composition of the two patterns rl and r2, obtained by taking the
union of nodes and edges, respectively, N(n) = N(wl )
U N(mz ) and E(T)
= E(7r1)
u E(m2); and
—S is the set of instances of the pattern n, obtained by composing the
instances in SI with those in Sz; two instances can be composed iff, for all
of the nodes (classes) N’ = N(ml ) n N(7Z ), they share the same object
instance.

Figure 6 gives an example showing the effect at the extensional level of the
composition operation. In Figure 6(a), the perspective P~ is shown defining a
filter over the “Laboratory,” and then in Figure 6(b) we see the effect of
composing P~ with the perspective Pz (Figure 5(b)).
Definition. Let PI(T ~,S1) and P2(m2, S2 ) be two compatible perspectives.
An overlay operation @ generates the perspective P(7, S) = PI @ Pz, where:
—*.=l.
fiz is the pattern; and
—S is the set of instances included in both of the perspectives, that is,
S={ SISGS1VS=S2).
This last operation is effective in getting pattern instances satisf~ng a
disjunction of conditions. In Figure 7(a) the perspective P4 is shown defining
a filter over the “Project Leader,” Next, in Figure 7(b) we see the effect of
overlaying P4 on the perspective P~ (Figure 6(a)). The overlay P3 fBP4
ACM Transactions on Information Systems, Vol 14, No. 1, January 1996.
-, ,,,
).
v. Lucare[la arm A. ~anzl
mrEEl
m.
I I
I
4- I
project
L1
/ “
Fig. 6. (a) Perspective P. with a filter over the laboratory. (b) Result of the composition
operation P2 @ P3.
Budget
T’

‘4
171
“ect
P3@P4
7 “
Fig. 7. (a) Perspective P4 witha filteroverthe projectleader.(b) Resultof the overlayoperation
P3 fBP4.
retains the instances in both of the perspectives, thus providing the research
projects either managed by the project leader P2 or developed in the labora-
tory LI.
The composition and overlay operations are very useful in combining
perspectives together and are simply activated by selecting the appropriate
icon button and then by dragging one perspective window upon the other. In
general, perspectives might be regarded as layers between the user and the
information system. Many perspectives can be available in order to have
different views on the same information network, each one focusing on some
information and hiding the rest.
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 17
3.4 Object Access
In order to access and view the objects in the instantiation of the perspective,
hrcwsing and navigation operations are available.
Definition, Given a perspective P( rr, S ), let c E N( n-) be a node (class). A
hrousing operation A’ returns all of the relative object instances) iff in-
cluded in one of the pattern instances s E S;
A’,(p)=
{olo=. Y(c) AoG ~(s)}.
Referring to the same example, by “clicking” on the node “Research Center,”
we get the content of this information node in the “presentation window.” By
default, simple attributes are embedded into the window with layout (e.g.,

font, color, size) derived from information set up during the loading (see the
next section ). Service buttons are then available for moving forward and
backward through the list of instances in the case of multiple instances.
Conversely, complex attributes are depicted in the window as “icon buttons”
that can then be activated in navigation mode. The effect of such operations
can be seen in Figure 11 (next section), where a display screendump is shown.
Definition, Given a perspective P( n, S ), let o be a displayed object in the
instance s E S, and let a be one of its complex attributes. Then a navigation
operation [” returns the linked object(s):
,/
.((),(P) = {o’l(o, a,o’)=.YAo’= N(s)}.
Note that the last condition in the definition prevents the user from accessing
nodes outside of the perspective. This is achieved dynamically by disabling
and masking those buttons pointing to objects out of the perspective.
Users may navigate from instance to instance according to their interests
by “clicking” on the “icon buttons”
representing the links. The navigation
operation allows access to the information nodes following direct links into
tbe perspective graph. Note that, in case of nodes involved in recursive
properties (e.g., “Research Project”), all of the matching instances are re-
turned by the browsing operation, whereas the joined projects can be reached
by navigating through the “joint” link.
Like many hypermedia systems, it is useful to have a “reverse button” in
order to follow reverse links. Given a node, this can be achieved by computing
the set of nodes linked to it in the pattern instances.
Definition. Given a perspective P( T, S), let o be a displayed object in the
instance s E S. A reLwrse navigation operation / ] returns the object(s)
linked to o:
,/ ‘(p) ={o/(o’,
a,o)G. YAo’ GI’V(,S )).

,,(, ))
Note that the operation returns all of the nodes pointing to the given one, and
it is not intended for going back to the previously visited node. Such a history
mechanism can be achieved, if requested, by maintaining a trace of the
visited object identifiers. In order to activate the rer,wrse-na[?igation opera-
A(’M Transaction. on information Systems.
\’1,1 1 i, NI) 1, J;inuary 19%
18 . D. Lucarella and A. Zanzi
tion, the user clicks on the “reverse button” in the presentation window, and
the system presents the user with the list of the attribute names pointing to
the given node in the perspective pattern. Once the requested one has been
selected, the instances of the objects pointing to it are returned.
The mechanism we have described in this subsection corresponds to the
usual way in which browsing and navigation through the information net-
work are accomplished in current hypermedia systems. The important differ-
ences are that (1) on the side of the user, such features are integrated into a
uniform interface so that a smooth shift becomes possible from querying to
browsing and vice versa and (2) on the side of the system, such features are
integrated and implemented using the same query-processing subsystem.
4. THE PROTOTYPE SYSTEM “MORE”
Since the focus in this article is on the visual interaction environment, only
an overview of the system architecture is provided, emphasizing those user-
oriented characteristics that have motivated this research project.
4.1 Design Overview
There is a general consensus in the field for separating the storage layer from
the application and presentation layers by creating a separate object data
server [Halasz and Schwartz 1994; Wiil and Leggett 1992]. According to this
trend, our system is composed of two cooperating subsystems that communi-
cate via a stream socket with the TCP/IP protocol.
Communication is established on a client/server basis, where the subsys-

tem MORE (Multimedia Object Retrieval Environment) [Lucarella et al.
1993] is the client process that requests object retrieval services to the
subsystem CORE (Complex Object Representation Environment). This is a
knowledge-based management system under development as a joint effort
between ENEL and the University of Milan. An outline of the system
architecture is given in Figure 8.
At present, CORE includes an efficient object management system that is
aligned to the requirements of the prototype implementation. In the future, it
will be substantially extended to become an intelligent multimedia object
server. The knowledge representation and manipulation language is based
on a tight integration between the object-oriented and logic programming
paradigm, and it is able to manage and query complex multimedia objects.
Essentially, we use a semantic object model as a conceptual front-end to the
CORE-like object base. As a possible alternative, cooperation with available
commercial object-oriented databases may be taken into account in the
future.
The MORE system supports schema creation and manipulation, informa-
tion loading and formatting, in addition to information filtering, browsing,
and navigation. The MORE environment takes advantage of the power-
ful semantic model upon which it is based and stresses, above all, ease of
comprehension and ease of use [Lucarella et al. 1994]. The main features
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 19
P
schema
user :
)
Editor
[
Pteaent. :

data ,
‘“e
MORE
R
schema& Pmpcct.
s
Manager
Le
ir
;:
r
Processor
s
e
m
a
n
t
i
c
Fig. 8. System architecture
characterizing the interaction environment are flexibility, reusability, and
consistency:
—Flexibility. Users differ from each other in terms of level of experience with
the task and in terms of frequency of use of the task. Our interface is
powerful and flexible enough to adapt to different situations. Graph-based
information representation and icon-based manipulation are attractive for
novices, but as shown before, also enable expert users to express complex
selection and filtering criteria.
—Reusability. Users are allowed to reuse definitions of objects already known

to the system. This is useful both in the schema design, in order to allow
incremental schema definition, and in the retrieval environment. In partic-
ular, evaluated perspectives can be saved with reference to a specific
information demand and reused later, either in the same way or modified
to build a new similar perspective.
—Consistency. Special care has been taken to use consistent modes of opera-
tion and the same interaction style when passing from one function to
another. The underlying semantic model provides a base for this consis-
tency. All operations are based on the same schema representation, and
the same graph-based manipulation paradigm is used in interacting with
the various system functions during both the design and operation phases.
The MORE system runs on IBM RISC/6000 workstations under the AIX
Operating System and AIXwindows. It has been developed by exploiting the
usual OSF/MOTIF facilities, such as icons, palettes, buttons, dialog boxes,
etc., and consists of the visual tools presented in the following subsections.
4.2 Editing Environment
The schema editor enables the application designer to create a schema graph
or to edit a previously created one, by picking icons from a predefine palette,
positioning and manipulating them directly into the associated window
ACM Transactions on Information Systems, Vol 14, N{,. 1, .January 1996
20 .
D. Lucarella and A. Zanzi
P
data
G
Sb.11’g
\
-1
[
%S,ls

l %-l 9
W!9
Fig. 9. Editing environment.
workspace. As shown in Figure 9, a limited number of icons in the palette is
sufficient to denote the actions that can be performed upon the primitive
components of the model. Depending on the icon selected, default actions are
activated, and/or an appropriate text entry window is presented.
The creation of a class requires the user to pick up the rectangular icon
from the palette, to position it in the workspace, and then to enter the class
name, with the system checking for the uniqueness of the name. In case of
primitive types, the oval icon is picked up and positioned, with the system
proposing a choice of built-in types. The same procedure is used for the
properties. The user picks up the icon corresponding to the desired property,
clicks on the nodes involved in the relationship, and then enters the label.
The sequence by which the nodes are touched affects the direction of the link.
It is possible and easy to affect the graphical layout of the schema by
dragging and moving around the objects afl.er their initial positioning or by
anchoring the graph and stretching or shrinking it. The deletion of nodes and
edges, regardless of the type, is achieved by picking up the respective icon
and then by clicking on the node/edge to be removed. Note that the deletion
of a rectangular node is achieved only if no incoming edges are present, and
when petiormed, it automatically implies the deletion of all outgoing edges
along with the oval nodes pointed to by such edges.
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 21
When saving the schema, validation functions are activated to check
whether the actual schema definition is consistent with the syntactic rules of
the model, thus preventing possible mistakes. If inconsistencies are detected,
they are graphically emphasized so that the user can easily identify the
problem and correct the schema accordingly.

Clearly, the visualization of the schema graph by the editor is limited by
the physical size of the screen. This may cause parts of the graph to be
offscreen, affecting the perception of the overall structure when the schema
increases in size. Presently, usual techniques including panning, zooming,
and scrolling are implemented; in the future the introduction of hierarchical
graphical abstractions will be considered, as suggeeted by Paulisch [1993], to
alleviate this problem.
4.3 Loading and Formatthg Environment
Once the load environment has been activated, and the desired schema has
been selected, the schema is presented to the user in a read-only window. It is
now possible, given a class, to load the object instances or to enter the
formatting specifications that will affect the presentation of all of the objects
belonging to that class.
The instance loader, activated through the corresponding icon, enables the
loading/updating of object instances according to the associated schema. The
user identities the object class by clicking on it, and an appropriate template
is presented in order to enter the values of the attributes for that instance,
with the system checking for type consistency, If a multivalued attribute is
present, two buttons are reported on the right that allow either the scanning
of the values already entered or the entry of new values.
Obviously, it is possible to have many loading templates at the same time
on the screen, and each template is equipped with back and forward buttons
to inspect the already loaded instances. In particular, this is useful when
managing complex attributes since, in this case, it is necessary to load the
object identifier of the referenced object. That can be easily achieved by
displaying in another template the object to be referenced (already loaded)
and then by dragging its identifier to the appropriate attribute slot. When the
template has been filled in, the object can be loaded, and the template can be
cleared for further loading. Validation checks are activated in this phase.
The format manager enables the entry of formatting specifications. A box

is associated with each class containing other boxes for each of the attributes
of the class. By clicking on a specific class, the associated box is presented by
default. It is now possible to interact for the definition of the layout (1) by
dragging and moving each box to the appropriate position and (2) by stretch-
ing each box to the appropriate size (this is also true for the outer box). At the
same time, it is possible to define the font to be used in case of string/text
attributes and the colors for the background/ fore~ound of the box. The same
facilities are available for the buttons associated with the links (complex
attributes) and with the labels of the attributes. In this phase, the box of the
attribute value is distinguished from the box of the attribute label by the
ACM Transactions on Information Systems, Vol, 14, No. 1, January 1996
22 . D. Lucareila and A. Zanzi
Fig.
10. Loadingandformattingenvironment.
presence of a star on the right of the string. Note that these specifications are
interpreted as layout constraints for attribute types that require special
processing (e.g., pictures, formatted documents, movies). To give a better idea
of such capabilities, an example of user-machine interaction is given in
Figure 10, referring to the object class “Manager.”
4,4 Retrieval and Presentation Environment
The retrieval enuirorzrnerzt provides the user with direct-manipulation facili-
ties for defining and operating on perspectives, as presented above. In the
retrieval environment, the user can directly access the object instances or,
conversely, can define a perspective in order to focus only on relevant
information. Such information can be filtered either to get optimal starting
points for navigation or to restrict the attention to a manageable subset of
objects.
Once entered into the environment, the selected schema graph is displayed
in a read-only window. The perspective is built inta the perspective window
by a sequence of “point-and-click actions on the classes in the schema graph.

The designated classes are copied into the perspective window together with
their attributes having as a domain primitive types. Namely, all oval nodes
pointed to by the designated node are copied by default. A click on an edge
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 23
will copy the participating classes, always with the same rule for the at-
tributes. If necessary, the user may later pick up additional nodes or remove
some of them. Once the user has built the desired perspective into the
perspective window, she or he proceeds with the specification of the filter.
After clicking on the class and relative attribute to be filtered, the required
conditions can be entered by using a corresponding text box presented by the
system.
After the filter is defined, a click on the select icon activates the function.
Unlike other interfaces in which the results of a query are returned in a form
inconsistent with the query, here the user gets the results as instances of the
perspective, thus maintaining the abstraction level provided by the model.
The presentation environment enables the user to display the object in-
stances. Simple attribute values are embedded into the presentation window
according to their formatting specification, whereas complex ones are repre-
sented by buttons with the label of that attribute. These buttons allow the
display of the instances of complex attributes through navigation. The pre-
sentation tool can be activated either on a perspective or directly on the
schema graph. In the latter case, all of the instances associated with a class
will be displayed one-by-one without any filtering performed by the perspec-
tive.
With reference to the application described previously, Figure 11 shows the
status of the display after a sequence of select and browsing operations. The
bottom “schema window” shows the conceptual schema graph; in the “per-
spective window,”
a filter has been specified corresponding to the request

“find the research projects dealing with the subject uisual languages and
developed at the laboratory named LINT.” Then, after clicking on the “Re-
search Project,” we see in the presentation window the first of the selected
instances, formatted according to the loaded specifications.
It should be clear now that all possible operations can be performed
symbolically and directly on the screen. The user does not need to know
either the syntax of the operations or which operation can be applied to which
objects. Thus, we reach the goal of decreasing the level of knowledge required
by the user, with the advantage of always maintaining the same uniform
interaction style.
5. RELATED WORK
In this section we briefly present related systems with emphasis on signifi-
cant differences between each of them and our system. In contrast to the
larger number of papers referenced in the introduction, here we focus our
attention on three systems that (1) have been proposed in the context of
hypertext/hypermedia applications and (2) are centered on a graph-based
data model and, hence, exhibit some features that overlap those of MORE.
GraphLog [Consens and Mendelzon 1990] is a logic-based query language
relying on a graph representation of data whose expressive power has been
proven to be equivalent to stratified linear DataLog. The further evolution,
the I-Iy
system [Consens and Mendelzon 1993], improves the data repre-
ACM Transactions on Information Systems, Vol 14. No. 1. .January 1996
24 s
D. Lucarella and A. Zanzi
-49.
.w
Y
P31-
-’L

41
Fig. 11. Retrieval and presentation environment
sentation by using hygraphs and provides a user interface with extensive
support for the visualization of large and tangled graph structures. Even
considering the more structured representation offered by the hygraphs, the
main difference with our system is that no concept of schema has been
introduced. Thus, no abstraction mechanism is available in the sense we have
introduced, such as types, generalization, complex objects, etc. As a conse-
quence, in GraphLog, queries can be specified only over the instance level,
but not over the schema level. In conclusion, the basic assumptions are
different, since they attack the problem of tangled structures by improving
the selection and visualization tools, whereas we try to overcome the problem
by improving the conceptual modeling capabilities.
GOOD [Gyssens et al. 1990] is an object-oriented database model in which
the schema as well as the instance of an object database is represented by a
graph, and the data manipulation is expressed by graph transformations
[Andries et al. 1992]. This transformation language has a graphical syntax
and semantics and contains basic operations for graph manipulations: addi-
tion/deletion of nodes/edges and abstraction, for grouping objects, according
to some of their properties. Essentially, the reported papers focus on theoreti-
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996
Visual Retrieval Environment for Information Systems . 25
cal issues with the main objective of setting up a framework for the imple-
mentation of a general-purpose data manipulation language. Only founda-
tions are discussed without proposing any visual interaction language so that
a comparison is difficult to be carried out. Conversely, our work is more
retrieval-oriented with the main purpose to make available a visual end-user
interface. In addition, our language is centered on the notion of perspective,
and the operations available for manipulating the perspectives, filtering, and
accessing the information have been strongly influenced by the requirement

of being really easy to use.
Gram [Amann and Scholl 1992] presents a graph-based model and query
language. The model is strongly typed, and a concept of schema has been
introduced; but there is no object orientation, in the sense we have intro-
duced, since nodes and edges are simply data types. Regular expressions over
the types of the nodes and edge labels are used to qualify walks (an alternat-
ing sequence of nodes and edges) in a graph. Central to the language is the
concept of )1.yperuwlk, a set of walks in the database graph sharing some
nodes, and defined by a hyperwalk expression. Hyperwalks might be consid-
ered close to our concept of pattern, but really they are different, since
patterns are subgraphs of the schema graph, whereas hyperwalks are linear
structures defined by regular expressions. Working on hyperwalks, Amann
and Scholl propose an algebraic query language, not yet implemented, that,
in our opinion, is not well suited for a visual interface. Conversely, it should
be noted that the Gram language, as well as GraphLog, is more expressive
than our visual language, which, at the moment, can be shown to be equiva-
lent to first-order logic plus transitive closure.
6. CONCLUSIONS
A very important problem in future large multimedia systems will be to
provide mechanisms that will allow the user to locate the desired information
efficiently and effectively. Extensions of the known technologies for databases,
information retrieval, and hypermedia will have to present a common model
able to accommodate the semantically rich structure of information, as
required in current hypermedia applications.
In this article we have presented a graph-based object model that has been
used as a uniform framework for visual information retrieval. These concepts
have been demonstrated in the implementation of the MORE prototype
system, which has been extensively tested in the context of a significant
hypermedia application. The considerations developed and experiments car-
ried out in a real setting suggest that the combination of a graph-based object

model with the direct-manipulation paradigm provides great flexibility for
conceptual modeling, as well as for the effective retrieval of multimedia
information. The visual interface is easy but powerful and flexible enough to
be suitable for different kinds of users, in terms of experience with the system
(naive vs. expert users) or in terms of frequency of use (casual vs. regular
users). The system has been proposed to a sample of different users with
A~M Transactions on Information Systems, Vol. 14, No 1, January 1996
26 . D. Lucarellaand A, Zanzi
previous experience with Query-by-Example systems as well as with hyper-
media systems, and MORE has been fairly accepted by all. In particular, the
same reported application had been previously implemented using a
widespread commercial hypermedia system. Despite being initially well ac-
cepted, essentially due to the easy interaction style, the system created many
problems because of the lack of selectivity in information access. With respect
to such users, MORE has represented a substantial improvement. The con-
cept of perspective has been easily understood. It has proven to be very
powerful and has been exploited also at the system management level for
delivering different parts of the information system to different groups of
users. In conclusion, although a research prototype, MORE shows consider-
able promise as an advanced information retrieval environment, in our
opinion.
Presently, the integration of advanced text-based retrieval techniques un-
der the same visual interface is in progress. As is well known from research
in the field, text retrieval is an inherently imprecise process [Salton 1989].
Very often, users are looking for information they do not know, so the request
becomes diflicult to formulate in terms of a rigid and unnatural boolean
notation. Furthermore, it is not effective simply to partition the set of objects
into objects that match the request and objects that do not, without mak-
ing any assessment of their presumed relevance to the needs of the user
[Guardalben and Lucarella 1993].

A considerable improvement can be achieved by enabling users to exploit
the notion of perspective and filter in constraining the search space and to
enter, in correspondence with text-type objects, a content profile reflecting
their own interests. The result will be that, during the filter specification,
when clicking on a text attribute, the user is allowed to enter a natural
language excerpt, describing in a rough way the interested subject. When
processing a request involving text-based filtering, the system applies a
best-match search strategy in order to locate the satisfying object instances
[Lucarella 19881. Best-match searching involves the identification of the
objects that are most similar to the submitted profile, with similarity being
measured by an appropriate closeness function. Retrieved object instances
are assigned a relevance score reflecting the degree of resemblance to the
user’s profile. So, during a following browsing operation, they can be ranked
and presented to the user in decreasing order of presumed relevance. Obvi-
ously, such relevance scores affect the overall relevance of the patterns in
which text-type objects are included.
We plan in the long term to extend the functionalities discussed for
text-type objects to image-type objects as well. In the same way, during filter
specification, in correspondence with an image attribute, users should be
allowed to sketch in a visual way the main shape of the image they are
interested in, with the system returning the retrieved object instances ranked
in decreasing order of relevance. Our previous experiments have not been
completely satisfactory [DelBimbo and Lucarella 1991], but the results re-
ported by other authors seem to be promising [Hirata et al. 1993].
ACM Transactions on Information Systems, Vol. 14, No. 1, January 1996.
Visual Retrieval Environment for Information Systems . 27
ACKNOWLEDGMENTS
This work has been benefited by the efforts of many people. In particular,
thanks are due to Cristina Raspollini from the IBM Research Center in Rome
for the support given in the frame of a cooperation agreement; Aurelio

Lanparone and Stefania Costantini from the Information Science Department
of the University of Milan for their research activity on logic-based modeling;
Stefano Parisotto and Mauro Zanzi from the same university for the research
and programming efforts carried out during the development of their doctoral
theses; and John Leggett from the Computer Science Department of Texas
A & M University for his suggestions concerning an early version of this
article that gave us the chance to improve the system and the article.
REFERENCES
.4FRATI, F. mm KOUTRAS, D. 1990,
A hypertext model supporting query mechanisms. In
Hypertext: Concepts, Systems,
and Applications, A.
Rizk, N, Streitz, and J. Andr&, Eds.
Cambridge University Press, Cambridge, Mass., 52-66,
AMAXN, B. ANDSCHOI.L,M. 1992. Gram: A graph data model and query language. In Proceed-
ings of the ACM Conference on Hypertext (Milan, Italy). ACM, New York, 201 –211.
ANDRJES,M., GIIMIS,M., PAREDAENS,J., THYSSENSI., AfSDV,m DENBUSSCHE,J. 1992. Concepts
for graph-oriented object manipulation, In Aduances in Database Technology, A. Pirotte, C,
Delobel, and G, Gottlab, Eds. Lecture Notes in Computer Science, vol. 580. Spnnger-Verlag,
Berlin, 21-38,
.Mw;~:[AvcR~, M., CATAR(’I.T., AIVUS.WTUWI, G, 1990. QBD*: .4 graphical query language with
recursion. IEEE Trans. Softw. Eng. 16, 10, 1150-1163,
Aron]xo, A., AMI~L, E., ANOBH.W;AVA, B. 1991. Experiences with SUPER, a database visual
environment. In Proceedings of the 2nd International Conference on Database and Expert
Systems. Springer-Verlag, Berlin, 172-178.
BAT[~[, C., CA~AR(’1, T., COSTAIMLE,M. F., AND LEVIALDI,S, 1992. Visual query systems: A
taxonomy. In Visual Database Systems 11, E, Knuth and L. M. Wagner, Eds. North-Holland,
Amsterdam, 153-168.
BwR], C. 1990. A formal approach to object-oriented databases, IEEE Data Knowl, Eng. 5, 4,
353-382.

BEER], C, AhW KOR~A’IXKY, Y,
1990. A logical query language for hypertext systems. In
Hypertext: Concepts, Sy.$tems, and Applications, A. Rizk, N. Streitz and J. Andre, Eds.
Cambridge University Press, Cambridge, Mass,, 67-80.
BELKIN, N. J, ANDCROFT, W. B, 1992. Information filtering and information retrieval: Two
sides of the same coin? Commun, ACM 35, 12 (Dec.), 29-38.
BFRTIM)) E., NWRI, M., PWWATTI, G., AND .’%ATTELLA,L. 1992. Object-oriented query lan-
guages: The notion and the issues, IEEE Data Knowl. Eng, 4, 3, 223-237.
BRYrK, D, ANDHL’LL, R. 1986. SNAP: A graphics-based schema manager. In Proceedings of the
IEEE Conference on Data Engineering (Los Angeles, Calif.). IEEE, New York, 151-164.
CmPRix,L, B. ANDGOOOMAN,J, 1988. HAM: A general purpose hypertext abstract machine.
Commun. ACM 13, 7 (July), 856-861,
CATARCT,T. 1992. On the expressive power of graphical query languages. In Visual Database
Systems 11, E. Knuth and L. M. Wagner, Eds, North-Holland, Amsterdam, 411-421,
CHRJSTOLXJJLAKIS,S., THEOnORJIXXl,M,, Ho, F., PAPA, M., ,om PATHRJA,A. 1986. Multimedia
document presentation, information extraction, and document formation in MINOS. ACM
Trans. Off. Inf. S.yst. 4, 4, 345-383.
CoNswIM B. 1987. Hypertext: An introduction and survey. IEEE thnpu~. 20, 19, 17-41.
Co~Sh:~s, M. P, .mn MENDELZON,A. 1993. Hy +: A hygraph-based query and visualization
system. In Proceedings of the ACM SIGMOD Conference (Washington, D.C. ). ACM, New York,
511 516.
ACM Transactions on Information Systems, Vol. 14, No 1, January 1996.