NoteCards is a general hypermedia environment designed to help people work with ideas. Its intended users are authors, designers, and other intellectual laborers engaged in analyzing information, designing artifacts, and generally processing ideas. The system provides these users with a variety of hypermedia-based tools for collecting, representing, managing, interrelating, and communicating ideas. This paper presents the NoteCards system as a foil against which to explore some of the major limitations of the current generation of hypermedia systems. In doing so, this paper highlights seven of the major issues that must be addressed in the next generation of hypermedia systems. These seven issues are: search and query, composite nodes, virtual structures, computational engines, versioning, collaborative work, and tailorability. For each of these issues, the papers describes the limitations inherent in NoteCards and the prospects for doing improving the situation in future systems.

Currently, a variety of information retrieval systems are available to potential users. These services are provided by commercial enterprises (such as Dow Jones [6] and The Source [7]), while others are research efforts (the Boston Community Information System [S]). While in many cases these systems are accessed from personal computers, typically no advantage is taken of the computing resources of those machines (such as local processing and storage). In this paper we explore the possibility of using the user’s local storage capabilities to cache data at the user’s site. This would improve the response time of user queries albeit at the cost of incurring the overhead required in maintaining multiple copies. In order to reduce this overhead it may be appropriate to allow copies to diverge in a controlled fashion. This would not only make caching less costly, but would also make it possible to propagate updates to the copies more efficiently, for example, when the system is lightly loaded, when communication tariffs are lower, or by batching updates together. Just as importantly, it also makes it possible to access the copies even when the communication lines or the central site are down. Thus, we introduce the notion of quasi-copies, which embodies the ideas sketched above. We also define the types of deviations that seem useful, and discuss the available implementation strategies.

A database design methodology is defined for the design of large relational databases. First, the data requirements are conceptualized using an extended entity-relationship model, with the extensions being additional semantics such as ternary relationships, optional relationships, and the generalization abstraction. The extended entity-relationship model is then decomposed according to a set of basic entity-relationship constructs, and these are transformed into candidate relations. A set of basic transformations has been developed for the three types of relations: entity relations, extended entity relations, and relationship relations. Candidate relations are further analyzed and modified to attain the highest degree of normalization desired. The methodology produces database designs that are not only accurate representations of reality, but flexible enough to accommodate future processing requirements. It also reduces the number of data dependencies that must be analyzed, using the extended ER model conceptualization, and maintains data integrity through normalization. This approach can be implemented manually or in a simple software package as long as a “good ” solution is acceptable and absolute optimality is not required.

The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling and maintenance, query optimization, and data

Conventional software systems, such as those based on the "desktop metaphor," are ill-equipped to manage the electronic information and events of the typical computer user. We introduce a new metaphor, Lifestreams, for dynamically organizing a user's personal workspace. Lifestreams uses a simple organizational metaphor, a time-ordered stream of documents, as an underlying storage system. Stream filters are used to organize, monitor and summarize information for the user. Combined, they provide a system that subsumes many separate desktop applications. This paper describes the Lifestreams model and our prototype system. I. Introduction I NEXPERIENCED users are right to be confused by today 's operating systems; they aren't well suited to most users needs and they require too many separate applications, too many file and format translations, the invention of too many pointless names and the construction of organizational hierarchies that too quickly become obsolete. They are built on id...

A view in object-oriented databases (OODB) corresponds to virtual schema graph with possibly restructured generalization and decomposition hierarchies. We propose a methodology, called MultiView, for supporting multiple such view schemata. MultiView represents a simple yet powerful approach achieved by breaking view specification into independent tasks: class derivation, global schema integration, view class selection, and view schema generation. Novel features of MultiView include an object algebra for class customization; an algorithm for the integration of virtual classes into the global schema; a view definition language for view class selection, and the automatic generation of a view class hierarchy. In addition, we present algorithms that verify the closure property of a view and, if found to be incomplete, transform it into a closed, yet minimal, view. Lastly, we introduce the fundamental concept of view independence and show MultiView to be view independent.

A specific query establishes a rigid qualification and is concerned only with data that match it precisely. A vague query establishes a target qualification and is concerned also with data that are close to this target. Most conventional database systems cannot handle vague queries directly, forcing their users to retry specific queries repeatedly with minor modifications until they match data that are satisfactory. This article describes a system called VAGUE that can handle vague queries directly. The principal concept behind VAGUE is its extension to the relational data model with data metrics, which are definitions of distances between values of the same domain. A problem with implementing data distances is that different users may have different interpretations for the notion of distance. VAGUE incorporates several features that enable it to adapt itself to the individual views and priorities of its users.

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Scientific research relies as much on the dissemination and exchange of data sets as on the publication of conclusions. Accurately tracking the lineage (origin and subsequent processing history) of scientific data sets is thus imperative for the complete documentation of scientific work. Researchers are effectively prevented from

The automated discovery of knowledge in databases is becoming increasingly important as the world's wealth of data continues to grow exponentially. Knowledge-discovery systems face challenging problems from real-world databases which tend to be dynamic, incomplete, redundant, noisy, sparse, and very large. This paper addresses these problems and describes some techniques for handling them. A model of an idealized knowledge-discovery system is presented as a reference for studying and designing new systems. This model is used in the comparison of three systems: CoverStory, EXPLORA, and the Knowledge Discovery Workbench. The deficiencies of existing systems relative to the model reveal several open problems for future research.