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Project promotion materials:

Data collections can be seen on:

https://researchdata.ands.org.au/search#!/group=Queensland University of Technology/class=collection

Data Management Policy/Procedure:

https://www.library.qut.edu.au/research/data/management.jsp

Project Members:

Colin Eustace (c.eustace@qut.edu.au)

Data Librarian (jodie.vaughan@qut.edu.au)

ANDS Contact:

Andrew White (andrew.white@ands.org.au)

Project Status:

Completed

Open Access Spatial Data and Collaboration - Queensland University of Technology Major Open Data Collections Project

Queensland University of Technology

Project Description

The Major Open Data Collection (MODC) project delivered support to multi-disciplinary collaborative research activities through partnership building between QUT researchers and Queensland government agencies, in order to add to and promote the discovery and reuse of a collection of spatially referenced datasets. Descriptions for the datasets allow researchers to demonstrate and answer questions in agriculture, construction, culture, education, tourism, resources and the science sectors.

The MODC project built upon existing Research Data Finder infrastructure (which uses VIVO open source software, developed by Cornell University) to develop a separate collection, Spatial Data Finder(https://researchdatafinder.qut.edu.au/spatial) as the interface to display the spatial data collection.
During the course of the project, 62 dataset descriptions were added to Spatial Data Finder, 7 added to Research Data Finder and two added to Software Finder, another separate collection. The project team met with 116 individual researchers and attended 13 school and faculty meetings to promote the MODC project and raise awareness of the Library’s services and resources for research data management.

A highly anticipated data release, amongst the QUT research community and beyond, was data generated through building sensors located throughout QUT’s Science and Engineering Centre (SEC). Designed as a "smart building", the SEC has cameras and sensors embedded throughout. They are constantly recording a high volume of time-stamped data about lift usage, network usage, power consumption, solar power generation, air conditioning, temperature, human traffic, and more. Software has been specifically written to collect, organise and store feeds of structural data, subsurface data and vibration data onto QUT's storage systems. Records for the three types of data captured from the SEC are published in Spatial Data Finder.

The Smart Transport Research Centre (STRC) is a world-class research centre at QUT, collaborating with the Department of Transport and Main Roads (TMR) and Brisbane City Council (BCC), utilising open transport related spatial data to improve traveller information systems and allow users to make informed decisions about their commute. The project team entered into an agreement with the Department of Transport and Main Roads to describe the large collection of mobile and aerial laser scanning data stored on QCIF infrastructure, to improve discoverability and facilitate re-use.

The creation of the metadata records for this collection will continue in an ongoing manner.

Data Type:

geospatial data

ANZSRC-FOR code:

0701 AGRICULTURE
LAND AND FARM MANAGEMENT
0905 CIVIL ENGINEERING
0401 ATMOSPHERIC SCIENCES
1904 PERFORMING ARTS AND CREATIVE WRITING
1506 TOURISM