Data Management: Documentation & Metadata Sherry Lake, Senior Data Consultant Bill Corey, Data Consultant Jeremy Bartczak, Intellectual Access & Metadata.

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Presentation transcript:

Data Management: Documentation & Metadata Sherry Lake, Senior Data Consultant Bill Corey, Data Consultant Jeremy Bartczak, Intellectual Access & Metadata Services Librarian © 2013 by the Rector and Visitors of the University of Virginia. This work is made available under the terms of the Creative Commons Attribution-ShareAlike 4.0 International license

Documentation & Metadata Agenda: Metadata: What is it? Why is it important? Capturing and managing metadata: –Best practices –Tools Hands-On Creation of Metadata Questions

Metadata in Everyday Life DataONE Education Module: Metadata. DataONE. Retrieved Nov 12, From CC image by USDAgov on FlickrCC image by Mskadu on Flickr Author(s) Boullosa, Carmen. Title(s) They're cows, we're pigs / by Carmen Boullosa Place New York : Grove Press, Physical Descr viii, 180 p ; 22 cm. Subject(s) Pirates Caribbean Area Fiction. Format Fiction Author(s) Boullosa, Carmen. Title(s) They're cows, we're pigs / by Carmen Boullosa Place New York : Grove Press, Physical Descr viii, 180 p ; 22 cm. Subject(s) Pirates Caribbean Area Fiction. Format Fiction

Metadata What is it? –Structured information that describes a resource Why is it important? –Enables a resource or data to be easily discovered –Good metadata will help others understand and use your data

Information Entropy DATA DETAILS Time of data development Specific details about problems with individual items or specific dates are lost relatively rapidly General details about datasets are lost through time Accident or technology change may make data unusable Retirement or career change makes access to “mental storage” difficult or unlikely Loss of data developer leads to loss of remaining information TIME (From Michener et al 1997)

Metadata Answers… Who created the data? Who maintains it? When were the data collected? When were they published? Where was it collected (geographic location)? What is the content of the data? The structure? Why were the data created? How were they produced/analyzed?

Metadata in Research Project DocumentationDataset Documentation Context of data collection Data collection methods Structure, organization of data files Data sources used Data validation, quality assurance Transformations of data from the raw data through analysis Information on confidentiality, access and use conditions Variable names and descriptions Explanation of codes and schemas used Algorithms used to transform data File format and software (including version) used

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

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

Metadata Formats Documentation for understanding & re-use –Readme File –Data Dictionary –Codebook Structured documentation in XML format for use in programs –DDI –FGDC –EML

Unstructured Documentation Data Dictionary ReadMe File Dryad Example (lab notebook) b_example_readme.pdf Google Forms

Structured XML Standard Schemes (XML) –DDI– Data Document Initiative –FGDC– Geospatial Metadata Standard standards –EML– Ecological Metadata Language

Metadata Concept Map by Amanda Tarbet is licensed under a Creative Commons Attribution- NonCommercial-ShareAlike 3.0 Unported License. Metadata Standards

Structured Metadata Tools Tools –Colectica add-on for Excel (DDI) –Nesstar (DDI) –Metavist (FGDC) –Morpho (EML)

Colectica for Excel Excel Addin (DDI) Describes data files, variables, and code listings (metadata saved in the excel file) Import SPSS (.sav) & Stata (.dta) files into Excel, along with metadata Code books can also be customized and generated by the tool with various outputs cel

Nesstar Publisher DDI Metadata Editor Creates codebooks ml

Metavist Metadata editor for FGDC Includes fields for the Biological Data Profile

Morpho Data Management Software Creates EML metadata Create a catalog of data & metadata upon which to query, edit and view data collection Easy-to-use, cross-platform application for local and network access

QUESTIONS? Sherry Lake, Senior Data Consultant Bill Corey, Data Consultant Jeremy Bartczak, Intellectual Access & Metadata Services Librarian. Health Sciences Library Data Management Consulting Group