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Digital Humanities: Data

Getting Started

Planning

Finding

Cleaning

Advice on research methodology : Ben Daniel

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Do more

University of Otago Solutions

Some Examples of Registries and Repositories of Open Data

Other sources of data specific to your discipline are often included in Subject Guides.

Also see Spatial Data (in Tools>GIS)


Digitised Primary Sources and Datasets 

Also see Text Mining

Can I harvest data from any other Library Database?

Many of the databases the Library subscribes to do not allow unsolicited text/data harvesting in their licenses.  Some will allow researchers to negotiate access (sometimes for a fee).  Please consult with your Subject Librarian before attempting automated data scraping and large­ scale access to journal articles and databases as part of your project.


Digitalised Newspapers


What is Open Data?

Otago ITS supported software for qualitative analysis:


Otago ITS supported statistical analysis applications:


Using R to Analyze your Data


Need More Computing Power?


Also see:

 

Select a Data Repository


Upload and Share Your Data 


Need to Control Who You Share Data With?


Publish in a Data Journal


Get a DOI for your Data


Move Large Amounts of Data

How to Cite Data


Get a DOI for your Data

Cleaning Data Guides


OpenRefine (formally Google Refine)

OpenRefine: Digital Humanities focused tutorial

Learn the basics

Tools to create beautiful visualisations:

See Visualisation (in Tools)

See Create Maps (in Tools>GIS)


Be Inspired

Sources of Open Statistical Data

Other sources of statistical data specific to your discipline are often included in Subject Guides.


Integrated Data Infrastructure (IDI)  and Confidentialised Unit Record Files (CURFs)

Contact access2microdata@stats.govt.nz for further information on data location, security, privacy and confidentiality. From 1 July 2014 data access costs will be reduced and new remote access locations set up. Overview page - Access our microdata.

Learn more about the IDI, CURFs and other sources of New Zealand Statistics, by visiting Statistics for Research on the Library's NZ Statistics guide.

You can also consult Thelma Fisher, Contact Officer for Statistics NZ at the University of Otago.

Data Mining / Text Mining

Data or Text mining is where computer software applies automated analytical techniques to interrogate data sets for patterns, trends and other useful information that typically would be incredibly labour intensive or difficult to conceive by traditional human research.


Learn more


Digitised Primary Sources and Datasets

Can I harvest data from any other Library Database?

Many of the databases the Library subscribes to do not allow unsolicited text/data harvesting in their licenses.  Some will allow researchers to negotiate access (sometimes for a fee).  Please consult with your Subject Librarian before attempting automated data scraping and large­ scale access to journal articles and databases as part of your project.


What tools are available for text analysis and topic modeling?

See Text mining & analysis


New to APIs? Learn more:


New Zealand API examples: 


Other API examples:


API Directory:


If you are interested in whether a specific Library database has an API please contact your Subject Librarian.

Experimenting with the British Library’s content and data - DHA Praxis project

Be inspired!

In February 2016, the University of Nottingham and British Library Labs organised the workshop “Experimenting with the British Library’s Content and Data” as part of the British Library Labs Roadshow 2016 and the Digital Humanities and Arts Praxis Project. Researchers from the Horizon Digital Economy Research Institute and the British Library Labs team presented experiences of creative use of digital collections and data. The workshop ended with the ‘Ideas Lab’ encouraging participants to explore, experiment and think of ideas of what they might do with the British Library’s digital content and data. This video presents a synthesis of the event.

We want your feedback!

This guide continues to evolve, and we really welcome your feedback so we can continue to improve it. Please let us know if you find:

  • Incorrect or irrelevant details, tools that don't work, dead links or otherwise unhelpful information
  • Helpful details, tools, links or information that you think need to be on the guide, but aren't currently.

We'd also love to hear from you if you want to have your project featured on the guide, or would like to be profiled on the Connect&Collaborate@Otago page. Email Alexander Ritchie, or Antje Lubcke with any comments or suggestions on how we can improve it.

Viva Digital Humanities!