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Databases

Databases. PGCE Secondary SS School of Education University of Southampton. Databases. A database is a collection of data, with common features – eg telephone directory Two main characteristics, being fields and records data fields define the kind of information

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Databases

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  1. Databases PGCE Secondary SS School of Education University of Southampton

  2. Databases • A database is a collection of data, with common features – eg telephone directory • Two main characteristics, being fields and records • data fields define the kind of information • Records are distinct sets of information • Electronic databases have distinct advantages over paper based databases, being…

  3. Power of electronic databases • The ability to add and edit records and data quickly • The ability to sort records by any field • The ability to select specific kinds of records • The ability to turn opaque data into understandable and useful information very quickly

  4. 4 records sorted by name Four fields - name, street, town and mobile 4 of 20 records sorted by name, Anderson through to Davidson

  5. 4 records sorted by town Four fields - name, street, town and mobile 4 of 20 records sorted by town, Doncaster through London

  6. Selection of Southampton Records Four fields - name, street, town and mobile Only the three Southampton records have been selected. They are sorted by name. Nested sorts are possible.

  7. Examples of Databases • Electronic directories • Email address book, browser history… • Government data • National Insurance register, passport register, drivers licence register… • Student database of SU • Search Engine results • Web crawlers, collecting email addresses and info re websites viewed

  8. Children using databases • Collections such as • Music • Music Match, mp3 players • Stamps • Directory of numbers on mobile telephones, handheld computers etc • Search engine results

  9. Database Software • Flat, one dimensional such as Pinpoint, Rapidfile • See one set of data at a time • Simple and easy to use • Relational database like Access and other specialist software • Linked data from a number of datasets • Eg – Govt registers linking tax, national insurance, passport, driving licence and other data

  10. Making sense of opaque data • Albany Graveyard Database • How clear is the raw data? • What questions can we ask of the date to make sense of it? • How can we make the findings clear? • How generalisable are the findings?

  11. Albany graveyard Database Field work and data query of Albany graveyard data by schools in the Albany area of the Eastern Cape, SA

  12. Issues to consider… • DB’s powerful, but can be abused by compilers • What info requested, and what for? • Cost to the provider of data that can be ‘used’ against them • Papertrails, unsolicited mail, scams, popups, spam… • Privacy of information issues… • 1984, 666…

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