1 / 7

Data Management: Documentation & Metadata

Understand the importance of data documentation and metadata for data reuse, sharing, and project success. Learn critical roles and elements of documentation to enhance data discovery, retrieval, archiving, and analysis. Discover essential details and methods for documenting data throughout your research process.

laub
Download Presentation

Data Management: Documentation & Metadata

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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/

More Related