Class exercise - collecting data - individual

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Presentation transcript:

Class exercise - collecting data - individual Peter Fox Data Science – ITEC/CSCI/ERTH-6961-01 Week 4, September 20, 2011

Modes of collecting data, information Observation Measurement Generation Driven by Questions Research idea Exploration

Management Creation of logical collections Physical data handling Interoperability support Security support Data ownership Metadata collection, management and access. Persistence Knowledge and information discovery Data dissemination and publication Derived from Data Management Systems for Scientific Applications IFIP Conference Proceedings; Vol. 188 Proceedings of the IFIP TC2/WG2.5 Working Conference on the Architecture of Scientific Software Pages: 273 - 284 Year of Publication: 2000 ISBN:0-7923-7339-1 Reagan Moore Kluwer, B.V. Deventer, The Netherlands, The Netherlands

Practical details for this week Preparation was your plan (A1) and some of you have feedback This week is practical – scope your effort so that you can ~ conduct it within class hours if possible (not required) Ground rules ONE data collection options No one off collections This is an individual exercise

What you tripped over New data collection Logical collections (please notice plural) Will - versus if/could/would Specific versus generic (need details) Not enough searching on data formats, metadata, standards, etc.

Practical details for this week (ctd) A write up will be required, details are in Assignment 2 and presented in weeks 5 and 6 (i.e. keep detailed notes) No analysis is required Questions? What are you planning to do?

What is next Assignment 2 is due next week (written) Presentation is due after the class you present it in No reading this week Participation for the next two weeks is very important as you will learn a lot from your peers

Presenting your data ~10 min each Split over two weeks but all need to be prepared to present next week 4-5 slides MAX Present The goal, and the mode of collection How data was acquired Physical and logical organization Other ‘management’ aspects Metadata and documentation collected/ stored Some data in some form