The purpose of this paper is to present a concept of the protocol for public registries based on blockchain. New database protocol aims to use the benefits of blockchain technologies and ensure their interoperability.
This paper is framed with design science research (DSR). The primary method is exaptation, i.e. adoption of solutions from other fields. The research is looking into existing technologies which are applied here as elements of the protocol: Name-Value Storage (NVS), Berkley DB, RAID protocol, among others. The choice of NVS as a reference technology for creating a database over blockchain is based on the analysis and comparison with two other similar technologies Bigchain and Amazon QLDB.
The proposed mechanism allows creating a standard database over a bundle of distributed ledgers. It ensures a blockchain agnostic approach and uses the benefits of various blockchain technologies in one ecosystem. In this scheme, blockchains play the role of journal storages (immutable log), whereas the overlaid database is the indexed storage. The distinctive feature of such a system is that in blockchain, users can perform peer-to-peer transactions directly in the ledger using blockchain native mechanism of user access management with public-key cryptography (blockchain does not require to administrate its database).
This paper presents a new method of creating a public peer-to-peer database across a bundle of distributed ledgers.
As yet, the services and guides offered commercially do not address the problem of database selection fully. There is a need for a database selector that can either take database selection out of the hands of the inexperienced or act as an advisor to more experienced online users. One approach to assisting business database selection is to produce better software, but of what type? Examination of the problem suggests that an expert system, which embodies and applies problem‐solving skills, might be suitable, since the task of database selection requires specific cognitive skills; intermediaries with skills in selecting databases exist; and intermediaries can articulate the methods they use to select databases.
The characteristics and advantages of database machines are summarized, and the application of database machines to library functions is described, noting the ability to…
The characteristics and advantages of database machines are summarized, and the application of database machines to library functions is described, noting the ability to attach multiple hosts to the same database, as well as flexibility in choosing operating and database management systems for different functions without loss of access to a common database. See also a related article in the previous issue of Library Hi Tech.
Outlines two distinct views of database marketing – as a total marketing strategy and as a tactical tool. Argues that a database marketing strategy can be realized only in companies with a genuine customer focus. As a result the tactical choice is more appropriate to most companies. Suggests that the problems of database saturation, where further cross‐selling using a database is not cost‐effective, can be overcome through widening the company′s credibility as a supplier as well as by increasing the size of the database. A database marketing strategy uses the tools of image and brand building to establish this credibility.
To date, librarians have not produced a study comparing databases that are appropriate for political science research. This study compares the coverage, content, and retrieval methods for nine databases. The study uses sampling to evaluate search results for six topics, providing relevancy percentages for each database. The article also reviews the types of documents cited in these samples, and provides recommendations for matching each database to particular research needs.
A framework based on the database entropy concept developed for characterizing the learning process of a database is applied to the dynamic measurement of the promptness…
A framework based on the database entropy concept developed for characterizing the learning process of a database is applied to the dynamic measurement of the promptness and coherence of a distributed database. The results can be of great value in the design and implementation of self‐adaptive distributed databases.
The value of downloading for database users is identified. These values are for temporary storage of data to repackage information and long term storage in newly created…
The value of downloading for database users is identified. These values are for temporary storage of data to repackage information and long term storage in newly created internal databases. The impact of these activities on the database producers and online vendors is discussed. Two factors which affect the volume of downloading are the availability of the technology and the legal implications of downloading. Several pricing policy solutions are mentioned.
Of the 3010 databases publicly available in 1985, 1,926 are classed as word‐oriented. The majority of these databases are available online either in the United States or elsewhere. Many are small and many are little used. Among online databases some 383 were active (used) in the information center/library market in the United States between 1982 and 1985. This market includes sixteen online search services (vendors). Databases accessed through those vendors have been continuously surveyed on a quarterly basis through the Information Market Indicators (IMI) survey since 1982. The vendors included in the survey are the major vendors of word‐oriented databases whose services are purchased by organizations in the United States. They are: BRS, Dialog, Dow Jones, Inform (VuText), ISI (Institute for Scientific Information, no longer active as a vendor), Legi‐Slate, MDC (Mead Data Central), NLM (National Library of Medicine), NYT (New York Times, no longer active as a vendor), Pergamon InfoLine, Questel, STN International, SDC (System Development Corp.), Source, Wilson‐line, and Westlaw. Data in this paper are based on the IMI survey.
A framework based on the entropy concept for characterizing the learning process of a database is developed. Such a framework can prove to be useful not only in analyzing…
A framework based on the entropy concept for characterizing the learning process of a database is developed. Such a framework can prove to be useful not only in analyzing existing databases and the design of self‐adaptive databases, but also in providing a basis for a unified approach to tackling a variety of related database problems.