By Paul Watson (auth.), Mike Jackson, David Nelson, Sue Stirk (eds.)
The British nationwide convention on Databases (BNCOD) was once demonstrated in 1980 as a discussion board for study into the idea and perform of databases. the unique convention within the sequence came about on the collage of Aberdeen. To be special, this convention was once in reality entitled ICOD which stood for overseas convention on Databases. It was once the goal, whilst the sequence begun, that an ICOD may occur each years, when a BNCOD may run within the years in among. because the list exhibits ICOD used to be simply held in 1980 and 1983. The extra junior convention has controlled to procure an entire life for much longer than that of its senior relative! If fact wereknown,however,BNCOD has,overthe years,growninto ICOD and even though the convention remains to be titled “British National,” it really is, actually, a world convention that occurs on a each year foundation. evidence of this is bought just by taking a look at the desk of contents of those continuing which clearlyshowthatthe majorityofpaperspresentedatthis year’sconferencecame from individuals whose a?liations are outdoors the united kingdom. Despitetherangeofpapersono?er,BNCODstillretainsitsuniquelyBritish ?avor. The Programme Committee is drawn from united kingdom lecturers and the c- ference is often held at a British college (or in previous years a polytechnic!).
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Extra resources for Database: Enterprise, Skills and Innovation: 22nd British National Conference on Databases, BNCOD 22, Sunderland, UK, July 5-7, 2005. Proceedings
Conventional data warehousing deals with alphanumeric data. In the real world, spatial data makes a large part of data stored in databases. It has been estimated that about 80% of such data has a spatial component to it, like an address or a postal code . In most data warehouses, spatial components are represented as a dimension table in the star schema. Time, is also an important dimension of every data warehouse, and it is usually represented as discrete points of time with appropriate hierarchy.
IEEE Transaction on Knowledge and Data Engineering, Vol. 12 No. 6 (2000) 938 – 957 17. Vassiliadis, P. Modeling Multidimensional Databases, Cubes and Cube Operations. Proc. of the 10th Int. Conf. on Sci. and Stat. Database Management (SSDBM), Italy, 1998. 18. Vassiliadis, P. and Sellis, T. A Survey of Logical Models for OLAP Databases. SIGMOD Record, Vol. 28 No. 4 (1999) TimeERplus: A Temporal EER Model Supporting Schema Changes Heidi Gregersen Department of Marketing, Informatics and Statistics, Aarhus School of Business, Fuglesangs All´e 4, DK-8210 Aarhus V Abstract.
Continuous vision of the user versus discrete vision of the computer cable to more domains and in new different ways. Continuous hypercube are structures that can be used for multidimensional analysis and exploration of data in a continuous manner. By the means of interpolation functions we will provide a continuous vision of the discrete hypercube and we will deal with the problems of missing and erroneous data. In this paper we presented the concepts, challenges and potentials of continuous data warehousing, and proposed a continuous multidimensional data model suitable for the analysis and exploration of continuous phenomena.
Database: Enterprise, Skills and Innovation: 22nd British National Conference on Databases, BNCOD 22, Sunderland, UK, July 5-7, 2005. Proceedings by Paul Watson (auth.), Mike Jackson, David Nelson, Sue Stirk (eds.)