Statistical Dissemination Systems and the Web

Statistical Dissemination Systems and the Web

Sindoni Giuseppe (Eurostat, Luxembourg) and Tininini Leonardo (CNR - Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Italy)
Copyright: © 2008 |Pages: 14
DOI: 10.4018/978-1-59904-857-4.ch053
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Abstract

The Web is increasingly used as a preferred medium for A2C (administration to citizens) and A2B (administration to business) service delivery. An increasing number of government initiatives are aimed at making access to electronic records easier for the general public. For example, the Electronic Record Archives program of the U.S. National Archives and Records Administration is aimed at preserving virtually any kind of electronic record, free from dependence on any specific hardware or software, and at enabling customers to find records they want and to deliver those records in formats suited to customers’ needs (Lake, 2006). This in particular will include records coming from the 2010 U.S. census. International professional associations are increasingly paying attention to public availability of statistical data. For example, the last meeting of the International Association for Social Science Information Services & Technology (IASSIST, 2006) dedicated entire sessions to problems like knowledge and resource discovery, innovative data dissemination systems, and data-intensive Web site design.

Key Terms in this Chapter

Fact Table: This is a table of reconciled elementary data (microdata in statistical terminology) to be grouped and aggregated in the process of data-cube construction.

Dimension: It is a property of data used to classify them and navigate the corresponding data cube. In data warehouses, dimensions are often organized into several hierarchical levels, for example, a time dimension can be organized into days, months, and years.

Data Cube: A data cube is a collection of aggregate values classified according to several properties of interest (dimensions). Combinations of dimension values are used to identify the single aggregate values in the cube.

Data Warehouse: A data warehouse is a repository of an organization’s data, specifically designed to support activities of analysis and decision making.

Metadata: According to the ISO (International Organization for Standardization) standard, it is defined as data that define and describe other data and processes.

Measure: The measure is a numeric value obtained by applying an aggregate function (such as count, sum, min, max, or average) to groups of data in a fact table.

Data Sharing: This is a data exchange process where open, freely available data formats and process patterns are known and standard. Thus, any organization or individual can use any counterparty’s data and metadata (assuming they are permitted access to it).

Drill-Down (Roll-Up): Drill-down is typical data warehouse operation by which aggregate data are visualized at a finer (or coarser for roll-up) level of detail along one or more analysis dimensions.

Statistical (Dissemination) Database: A statistical database is a database whose structure is specifically designed for the dissemination of statistical data (usually, but not necessarily, on the Web).

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