Transcript VIVO as an Institutional Dataset Registry

VIVO as an Institutional Data Registry
Philippa Broadley, Gawri Edussuriya, Lance De Vine, Stephanie Bradbury
Queensland University of Technology. Brisbane, Australia
Contact: [email protected]
VIVO at QUT
The Queensland University of Technology (QUT) in Brisbane, Australia, is involved in a
number of projects funded by the Australian National Data Service (ANDS). Currently,
QUT is working on a project (Metadata Stores Project) that uses open source VIVO
software to aid in the storage and management of metadata relating to data sets
created/managed by the QUT research community.
The registry (called QUT Research Data Finder) will support the sharing and reuse of
research datasets, within and external to QUT.
QUT uses VIVO for both the display and the editing of research metadata. Several
customisations to VIVO are under development to better facilitate it for its role as a
dataset registry. A general architecture with workflow consisting of a public facing
VIVO as well as a restricted access VIVO for data integration is in the final stages of
development (see Figure 1).
Research Data Australia
Figure 4. Collection record in Research Data
Australia (left).
NLA
Figure 5. Collection record in QUT Research
Data Finder (right).
Border firewall
Corporate firewall
OAI-PMH
Provider
Outbound request to
selected IP for minting
of identifiers.
Java
Application
Server
Several novel approaches have been used in the development with the anticipated
outcome that the process of importing and exporting data to and from VIVO will be more
efficient. For example, we have created DOI minting web application. Currently, the DOI
minting process in integrated with VIVO. This application will aid researchers in tracking
who is reusing their data sets and how they are being reused.
Research Data Finder
(VIVO)
MySQL
(Database)
SOLR
Data Librarian
Research
Master
Java
Application
Server
Research Data Finder
(VIVO)
MySQL
(Database)
ePrints ...
SOLR
Dataset Store
1
Transformation and Integration
Dataset Store
2
Staging and Data
Integration.
QUT has developed and will use a Java object model (CRMM) as an intermediate data
representation for data integration and transformation tasks (see Figure 6 below).
Figure 1. Architecture of the metadata capture and publishing system.
Key Outcomes of Metadata Stores Project
A public research profile portal (QUT Research Data Finder, beta version until
December 2012 - http://researchdatafinder.qut.edu.au/vivo/)
Workflow for registering new research data collections in the university
Alignment of metadata records about research activities with our institutional
research management system (ResearchMaster)
Alignment of metadata records about parties with an institutional name authority
e.g. QUT’s Staff Profiles system - http://staff.qut.edu.au/
Strategic reporting on contents and coverage of the metadata store (for internal
use)
As well as displaying records in QUT Research Data Finder, we will contribute
collection, party, activity and service records to Research Data Australia (ANDS’
discovery portal - http://researchdata.ands.org.au/) (see Figures 2 and 4).
Metadata mappings have been developed for various formats and mappings are
presently being constructed for moving data between CRMM and VIVO. The rationale
behind this is that the Java objects are relatively easy to manipulate, especially via high
level scripting languages that run on the JVM. Groovy technology was used for data
manipulation.
RIF-CS/XML
encapsulated
within OAIPMH
RIF-CS/XML
Transformation Scripts
Transformation Scripts
YAML (YAML
Ain’t Markup
Language)
VIVO Jena
Model
CRMM (placeholder
name) Java model
Transformation Scripts
Java Object
DB or RDB
Mapping
Mediaflux
Figure 6. Basic overview of metadata transformation and
integration using the Java Object Model (CRMM).
About ANDS
One of the chief goals of ANDS is to build the Australian Research Data Commons, a
cohesive collection of research data outputs from all Australian research institutions.
Funded by the Australian Commonwealth Government's Department of Industry,
Innovation, Science Research and Tertiary Education (DIISRTE), ANDS is engaged with
Australian universities to ensure that research data is better described, more connected,
more integrated and organised, more accessible and more easily used for new purposes.
This project is supported by the Australian National Data Service (ANDS)
Figure 2. Party record in Research data
Australia (left).
ANDS is supported by the Australian Government through the National Collaborative
Research Infrastructure Strategy Program and the Education Investment Fund (EIF) Super
Science Initiative.
Figure 3. Party record in QUT Research
Data Finder (right).
This work is licensed under a Creative Commons Attribution 3.0 Australia License.