Expressive Data Research Articles

The semiotics of expression in musical performance

Starting with the stark contrast between the power, subtlety and sophistication of performance expression and its systematic simplicity, this paper argues that the apparent contradiction can be reconciled by recognizing three important features: 1. the multi-faceted nature of the semiotics of performance; 2. the complex interaction between performance features and listeners' evolving structural interpretations; 3. the involvement of the body in the impact of musical performance, and of the somatic nature of music itself. This viewpoint is developed in the context of an analysis of expressive data from performances of the Prelude in E minor, op. 28 no. 4, by Chopin, coupled with a voice-leading analysis of the work itself.

Integrated access to metabolic and genomic data.

The EcoCyc system consists of a knowledge base (KB) that describes the genes and intermediary metabolism of Escherichia coli, and a graphical user interface (GUI) for accessing that knowledge. This paper addresses two problems: How can we create a GUI that provides integrated access to metabolic and genomic data? We describe the design and implementation of visual presentations that closely mimic those found in the biology literature, and that offer hypertext navigation among related entities, and multiple views of the same entity. We employ a frame knowledge representation system (FRS) called HyperTHEO to manage the EcoCyc knowledge base. Among the advantages of FRSs are an expressive data model for capturing the complexities of biological information, and schema-evolution capabilities that facilitate the constant schema changes that biological databases tend to undergo. HyperTHEO also includes rule-based inference facilities that are the foundation of expert systems, a constraint language for maintaining data integrity, and a declarative query language. A graphic KB editor and browser allow the EcoCyc developers to interactively inspect and modify this evolving KB.

PDB: A pictorial database oriented to data analysis

AbstractThe paper describes a new pictorial database oriented to image analysis, implemented inside the MIDAS data analysis system. Pictorial databases need expressive data structures in order to represent a wide class of information from the numerical to the visual. The model of the database is relational; however, a full normalization is not achievable, owing to the complexity of the visual information. The paper reports the general design and notes on the software implementation. Preliminary experiments show the performance of the pictorial database.

From database to information base: Some questions of semantics and constraints

The conceptual simplicity of the relational data model, and the widespread availability of database management systems based on that model, have greatly enhanced the accessibility of database technology. The design and implementation of a database is a model-building process. The components from which the final model (the database) is to be constructed are somewhat limited, and it follows that some characteristics of the ‘real world’ cannot readily be represented. In particular, the relational data model, and its commercial implementations, is poor in the areas of semantics and constraints; however, it is these semantics and constraints that make the difference between simple data and information. Although there have been a number of attempts to develop more expressive semantic data models, many of their advantages can be lost if the final implementation is to be in terms of the relational model. If the question of constraints is explored further, it becomes evident that the philosophy of the ANSI-SPARC architecture requires that these should form an integral part of the database, to be applied to all database transactions, and available for perusal as part of the meta-data. While performance criteria may lead to the constraint mechanism being a feature of an external interface, such decentralization can risk comprising database integrity. Finally, although the forthcoming revised standard for SQL will introduce a number of constraint mechanisms, it can be shown that a significant proportion of constraints that could be expressed in a ‘semantic’ data model will remain beyond the scope of SQL-2.

Semantic data models

Semantic data models have emerged from a requirement for more expressive conceptual data models. Current generation data models lack direct support for relationships, data abstraction, inheritance, constraints, unstructured objects, and the dynamic properties of an application. Although the need for data models with richer semantics is widely recognized, no single approach has won general acceptance. This paper describes the generic properties of semantic data models and presents a representative selection of models that have been proposed since the mid-1970s. In addition to explaining the features of the individual models, guidelines are offered for the comparison of models. The paper concludes with a discussion of future directions in the area of conceptual data modeling.

Application of SQL/N to the attribute-relation associations implicit in functional dependencies

SQL/N is an expressive nonprocedural data base language that is upward compatible with SQL. Its expressive power is derived from both the use of natural quantifiers and the quantification of subsets of relations, in particular the subsets that are the groups of related tuples that occur in associations between relations. We show that SQL/N is also very expressive in specifying requests involving attribute-relation associations, and that attribute-relation associations are implicit in functional dependencies. We show that an attribute-relation association may be derived from the association between an algebraic projection relation and the relation on which the projection operation is performed. Two common cases of attribute-relation associations are investigated: first the case of an association restricted to a single relation, and second a more general attribute-relation association where an attribute from one relation is associated with a second relation.

Views of office data

Office applications will eventually be defined and executed by office personnel rather than professional programmers. There are many scientific disciplines and technologies that are contributing to this goal. This panel will explore a few of these areas: databases, artificial intelligence, and linguistics. Today the active database research areas are in highly distributed, real-time transaction oriented systems, and dynamic expressive data organizations such as the relational model. The extending of the database models to cover the requirements of the office is a major concern in office systems research. Artificial Intelligence has been directly involved with the problems of interfacing with end-users for a considerable period of time. The AI knowledge base systems are much closer in spirit to the way humans accumulate and use partial knowledge to solve problems than the database models. Using AI techniques, expert systems have been built for various application areas. One can envision the use of expert office systems to help in solving business and organizational problems. Much of the communications done in the office is in terms of natural language. Linguistics is concerned with the structure of language and how people generate it and understand it. The greater the extent that an office system can deal with natural languages, the more useful that system will be to end-users. This panel will discuss how intelligent the next generation of office systems can become using these technologies.

Systematically Produced Intervention Strategies in Early Education

In recent years, instructional technology procedures have been utilized in developing various types of packaged curricula in the field of early education. This article describes the development of packaged curricula which address the broad skill areas of receptive and expressive language, motor, self-help and social emotional development Preliminary data regarding intervention effectiveness is presented.