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Data Management: Documentation & Metadata

Data Management: Documentation & Metadata. General Overview. Data Discovery. Data Archive. Re-Use. Deposit. Project Start Up. Proposal Planning Writing. Data Collection. Data Analysis. Data Sharing. End of Project. Re-Purpose. Data Life Cycle. Research Life Cycle.

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Data Management: Documentation & Metadata

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  1. Data Management:Documentation & Metadata General Overview

  2. Data Discovery • Data • Archive Re-Use Deposit Project Start Up Proposal Planning Writing Data Collection Data Analysis • Data • Sharing • End of • Project Re-Purpose Data Life Cycle Research Life Cycle

  3. Data Documentation (Metadata) • Informal or formal methods to describe your data • Important if you want to reuse your own data in the future • Also necessary when sharing your data

  4. Working with Data • When you provide data to someone else, what types of information would you want to include with the data? • When you receive a dataset from an external source, what types of details do you want to know about the data?

  5. Critical roles of data documentation • Data Use • To know enough details about how the how the data were collected and stored • Data Discovery • To be able to identify important data sets • Data Retrieval • To know how and where to access data • Data Archiving • Data can grow more valuable with time, but only if the critical information required to retrieve and interpret the data remains available

  6. Elements of Documentation Good data documentation answers these basic questions: • How were the data produced /analyzed? • Where was it collected (geographic location)? • When were the data collected? When were they published? • How should the data be cited? • Why were the data created? • What is the data about? • What is the content of the data? The structure? • Who created the data? • Who maintains it? • How were the data created?

  7. Documentation throughout your research UK Data Service: http://ukdataservice.ac.uk/media/440277/documentingdata.pdf/

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