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A survey of current work on database systems is presented. The area is divided into three main sectors: data models, data languages and support for database operations. Data models are presented as the link between the database and the real world. Languages range from formal algebraic languages to attempts to use a dialogue in English to formulate queries. The support includes hardware for content addressing, database machines and software techniques for optimizing and evaluating group expressions. Mathematical models are used to organize this support. Throughout there is a tutorial component and evaluation, which in both cases is related to the application of database ideas to documentation.

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for text retrieval. We analyse parallel IR systems using a classification defined by Rasmussen and describe some parallel IR systems. We give a description of the retrieval models used in parallel information processing. We describe areas of research which we believe are needed.

The connect hour prices for use of 320 online databases up on seven major biblio‐graphic systems in February 1981 in the U.S. and Canada were analyzed. A distribution was run and all databases fell into five ranges with 65% in the medium‐low ($25–49) and medium ($50–74) ranges. Government databases were analyzed as a subset of the total, and National Library of Medicine databases were analyzed in more detail as a subset of govern‐ment online databases. Further analyses of database prices were done in terms of four new measures: (1) price per connect‐hour per record accessible online; (2) price per connect‐hour per record searchable online; (3) number of records accessible per dollar per connect‐hour; and (4) number of records searchable per dollar per connect‐hour. Data are given in both real and constant dollars. Using these four measures, one can see that database size correlates extremely well with price. Reasons for increasing the price per connect hour for MEDLINE are given. They relate to the numerical analyses and to the responsibilities government database producers have to not‐for‐profit database producers.

The increasing availability of digital editions of journals, and/or the incorporation of the full‐text versions of their papers in the largest aggregator databases, have been the highlights in the coming of age of digital libraries from many perspectives, ranging from collection development to preservation, from ready reference services to creating digital carrels. Full‐text availability of research papers through several digital resources is not merely a great convenience for distributing knowledge, but also an indirect indicator of the acknowledgement of the popularity and importance of journals and other serial publications (such as conference proceedings) in many disciplines where such sources are the primary venues for scholarly and professional publishing. One of the purposes of the author's current research project was to find out how well three business databases reflect the popularity and familiarity of peer ranking and rating through 50 top rated marketing‐focused and marketing‐related periodicals in the full‐text coverage of those journals. This paper seeks to present some results.

The target journals were selected from the list of 50 marketing‐focused and marketing‐related journals ranked by nearly 630 faculty members from marketing departments of US and international universities in an outstanding large scale survey and research project by Hult et al. The presence and time‐span of coverage of 50 journals and conference proceedings was analysed in three of the largest (partially) full‐text business databases.

The research found that many highly rated and ranked journals in the sample were absent or very modestly present in the full‐text subset even in the largest and most widely licensed three business databases tested.

The research adds a new dimension to evaluating databases by the specific criteria of full text availability of journals and other serial publications.

This paper aims to provide a general overview, to be followed by a series of papers focusing on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus, and Web of Science) for determining the h‐index.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus and Web of Science).

The h‐index, developed by Jorge E. Hirsch to quantify the scientific output of researchers, has immediately received well‐deserved attention in academia. The theoretical part of his idea was widely embraced, and even enhanced, by several researchers. Many of them also recommended derivative metrics based on Hirsch's idea to compensate for potential distortion factors, such as high self‐citation rates. The practical aspects of determining the h‐index also need scrutiny, because some content and software characteristics of reference‐enhanced databases can strongly influence the h‐index values.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases.

One of the most important categories of data flow applications is databases — especially public databases. Without going into depth concerning the philosophy of database classification, in what follows we are going to describe and analyse the state of public database production and services in Hungary. All data and statistics that are used were published by the Hungarian Central Statistical Office (Orszagas Statisztikai Hivatal), the National Technical Library and Documentation Center (Orszagos Mueszaki Koenyvtar es Dokumentacios Koezpont—OMKDK) and by the Information Center for Construction and Building (Epitesuegyi Tajekoztatasi Koezpont) and in other printed publications. At this early point we would like to mention that OMKDK was recently reorganised and extended by new functions and now is called OMIK, but throughout the paper when mentioning this institution we refer to its old name, which was valid when the data for this study were collected.

The “collaboratory” concept has recently entered the vernacular of the scientific community to reflect new modes of scientific communication, cooperation and collaboration made possible by information technology. The collaboratory represents a scientific research center “without walls” for accessing and sharing data, information, instrumentation and computational resources. The principal applications of the collaboratory concept have been in the physical and biological sciences, including space physics, oceanography and molecular biology. Discusses the attributes of the collaboratory, and applies the concept developed by computer and physical scientists to the design and operation of the SIPPACCESS prototype information system for complex data to be used through the Internet by sociologists, demographers and economists. Examines obstacles to collaboratory development for the social sciences. Concludes that four major obstacles will inhibit the development of collaboratories in the social sciences.

Real estate appraisals are becoming an increasingly important means of backing up financial operations based on the values of these kinds of assets. However, in very large databases, there is a reduction in the predictive capacity when traditional methods, such as multiple linear regression (MLR), are used. This paper aims to determine whether in these cases the application of data mining algorithms can achieve superior statistical results. First, real estate appraisal databases from five towns and cities in the State of Paraná, Brazil, were obtained from Caixa Econômica Federal bank.

After initial validations, additional databases were generated with both real, transformed and nominal values, in clean and raw data. Each was assisted by the application of a wide range of data mining algorithms (multilayer perceptron, support vector regression, K-star, M5Rules and random forest), either isolated or combined (regression by discretization – logistic, bagging and stacking), with the use of 10-fold cross-validation in Weka software.

The results showed more varied incremental statistical results with the use of algorithms than those obtained by MLR, especially when combined algorithms were used. The largest increments were obtained in databases with a large amount of data and in those where minor initial data cleaning was carried out. The paper also conducts a further analysis, including an algorithmic ranking based on the number of significant results obtained.

The authors did not find similar studies or research studies conducted in Brazil.

This review reports on the current state and the potential of tools and systems designed to aid online searching, referred to here as online searching aids. Intermediary mechanisms are examined in terms of the two stage model, i.e. end‐user, intermediary, ‘raw database’, and different forms of user — system interaction are discussed. The evolution of the terminology of online searching aids is presented with special emphasis on the expert/non‐expert division. Terms defined include gateways, front‐end systems, intermediary systems and post‐processing. The alternative configurations that such systems can have and the approaches to the design of the user interface are discussed. The review then analyses the functions of online searching aids, i.e. logon procedures, access to hosts, help features, search formulation, query reformulation, database selection, uploading, downloading and post‐processing. Costs are then briefly examined. The review concludes by looking at future trends following recent developments in computer science and elsewhere. Distributed expert based information systems (debis), the standard generalised mark‐up language (SGML), the client‐server model, object‐orientation and parallel processing are expected to influence, if they have not done so already, the design and implementation of future online searching aids.

This paper describes the development of a fault‐tolerant database processor (DBP) system to replace OCLC's conventional file system, which not only improves overall system reliability and database availability, but also facilitates the operation and management of a large and rapidly growing online database. This database processor became operational on 16 October 1978, an achievement that represents a significant advance in the operation of information storage and retrieval systems.