Secondary Data Analysis

Post on 25-May-2015

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A paper presented at the IACSS2011 Symposium in Shanghai, September.

Transcript of Secondary Data Analysis

Secondary Data Analysis of the Asian Football Cup 2011:

Goal Scoring and FIFA Ranking

Keith LyonsUniversity of Canberra, Australia

• Increasing availability of public data …

• Supporting secondary data analysis …

• Raising questions about curation

Main Points of This Presentation

• 90 goals were scored in the whole Tournament.

• 64 goals were scored in 24 Group Games.

• 26 goals were scored in the 8 Knockout Games.

• December 2010 FIFA rankings were used to record performance against ranking in the Tournament.

• Higher ranked teams won 21 games, drew 4 games and lost 7 games.

• Saudi Arabia, Kuwait, China PR, Jordan and Australia lost to lower ranked teams.

The team that scored first won or drew 28 of 31 games played.

(There was one game that ended 0-0.)

• Researchers are able to access rich data about performance from websites …

• They are managing the risk of using these data services …

• The availability of these data will nourish the growth of secondary data and meta analysis research.

• In addition to the validity, reliability and accuracy of the data …

• There must be a strategic approach to the curation of Uniform Resource Identifiers (uri), Uniform Resource Locators (url) and Uniform Resource Names (urn) …

PURL

… are Uniform Resource Locators (urls) that act as permanent identifiers in the face of a dynamic and changing Web infrastructure.

This provides continuity of references to network resources that may migrate from machine to machine for business, social or technical reasons.

This brief paper is presented as a contribution to the discussion of consuming, learning about, creating and sharing web resources.

Produsing(Produce and Use)

We need to consider our roles as creators and curators of shared resources.