Rdsi project history slidedoc save pdf

RDSI
CREATINGAUSTRALIA’S
RESEARCHDATACLOUD

2|
TableofContents
03 12 20 35 39
Chapter I Chapter II Chapter III Chapter IV Chapter V
44 48 52 54 61
Chapter VI Chapter VII Chapter VIII Chapter XI Chapter X
IntheBeginning
Consultingthe
community
Thedatacollections
Anintegrated
infrastructure
Movingdata
Accessingdata Protectingdata Workingwithdata Selectingsolutions Casestudies
68 84
Chapter XI Chapter XI
Lookingbackand
lookingahead
Theteam

4|
…therewasnothing
At the very beginning of this
project there was nothing in the
sector for collaborative storage.
Really nothing. So it started
from scratch, to persuade people
that it was a good idea to store
data, except not just in your
university or in your research
group.
– Dr Nick Tate
RDSI Project Director

5|
Nodiscoverieswithout
data
RDSI is in my mind, entirely about the delivery
of data and the amassing of the data. It is my
belief that without bringing collections together,
without making them accessible, you can’t make
new discoveries.
‒ Prof Nathan Bindoff
Director TPAC and Professor of Physical Oceanography

6|
Howitstarted
There is growing recognition that new ways to conduct research have
emerged and are being validated across most research disciplines.
Adding to traditional forms of research that rely on experiment, theory
and testing hypotheses using data, it is now evident that researchers
also:
» collect increasingly larger sets of data as a primary form of research;
and
» use modelling tools to assist them in deriving patterns, perceptions and
trends that can form the basis for establishing and confirming
hypotheses.
Information and communications technology (ICT) is the cornerstone to
such new approaches, providing the means not only for increasingly
powerful computer-enabled simulation and modelling, but also the very
avenue to manage and integrate the increasing volume and complexity
of datasets and collections. Hence, ICT is not only a resource to
administer and manage research but also to drive and innovate the ways
in which research is conducted.
– Strategic Roadmap for Australian Research Infrastructure,2008, p19
In2008,theGovernment’sStrategicRoadmapfor
AustralianResearchInfrastructurehighlightedthe
needtomanageandintegratetheincreasingvolume
andcomplexityofresearchdatasetsandcollections.

7|
Researchstorage
beforeRDSI
Part of my role here at QCIF is to help research
groups with their storage needs. In the days
before RDSI it caught me by a huge surprise
that even at a major university it was quite
hard for a research group to get the right kind
of storage, to have some better way of
collaborating than sending a spreadsheet across
the globe.
I remember the first meeting I had with one
professor at UQ who had come from Oxford. He
said, ‘Look, I’m a centre director, I’m a
professor, and I have spent six months just
trying to get a little bit of storage. I’m worried I
should be doing something else.’
‒ Graham Chen
eResearch Manager, QCIF

8|
Researchstorage
beforeRDSI
A retiring academic in Marine Science came to
us at the University of Sydney library. He had
spent his whole life collecting data from the
beaches of Australia. He asked us, ‘What do I do
with all of this? It’s in various formats, it’s
valuable, but I don’t know what to do with it.’
We approached the university, but at that stage
the view was that when research results were
published, the research was finished. Why would
they want to store the data and why would
they want to share it?
‒ John Shipp
RDSI Project Board

9|
Researchstorage
beforeRDSI
We asked another researcher what she was
doing to curate her data. She said, ‘Every week I
download it onto CD. I make three copies: one
for home, one for the office, and one I send to
my mother in Perth.’
Even today I have a lingering fantasy that
somewhere in Perth there is a little old lady
with these CDs stacked up around her and one
day they will cave in on top of her and she will
be crushed by her daughter’s research. This is
just imagination, but it’s an indication of what
people were doing because they didn’t have
facilities to curate their data properly.
‒ John Shipp
RDSI Project Board

10|
2010:RDSIbegins
Dates:
2010-1014
Funding:
$50m
Program:
Education Investment Fund (EIF) under the Super Science
Initiative
Lead agent:
The University of Queensland
Chair:
Prof Max Lu
DeputyVice-Chancellor (Research)
Project Director:
Dr NickTate
The aim of the RDSI Project is that researchers will
be able to use and manipulate significant
collections of data that were previously either
unavailable or difficult to access, and that there will
be a consistent means of accessing this data.
The Project will be realised through the creation
and development of data storage infrastructure
accessed through a common infrastructure layer
and provided by agencies within the sector, or
commercial providers, or both.

11|
Whereshouldweput
thedata?
The question was, where should we put the
data? This was stopping progress across
research. People couldn’t keep storing it on
their desktops, and there were no onshore cloud
services at the time. That left us with two
options: either one big data centre or a small
number of sites around Australia. The problem
with one site is then you have to put everything
else around it, and you lose innovation. Several
is better.
‒ Dr Rhys Francis
RDSI Board

Consultingthe
community
Chapter II

13|
OpeningaDialogueJune
July
August
September
October
November
December
January
February
March
April
May
2011 2012
ReDS Consultation Series
9 Feb – 2 Mar
Vendor Briefing
1 Aug
ReDS Tinman
Consultation
28 Sep
DaSh Tinman
Consultation
11 Nov
ReDS Strawman
Consultation Series
3 June – 1 July
DaSh Strawman
Consultation Series
17 June

14|
Consultingthe
community
Because the Education Investment Fund has a
restriction that you can’t use the funding for
operation, we needed operational partners who
could provide the operational working funds. We
didn’t know if anybody would be interested in
putting their hand up to do that. We were
therefore consulting to see who would be
interested, under what circumstances they
might be interested, and what would be possible
for them to achieve that would meet the project
objectives and the needs of researchers. By doing
that we were able to put together a plan.
‒ Dr Nick Tate

15|
FromStrawMan
toTinMan
It was a large community engagement exercise.
For each program, we would find out who
might be interested, get them together for a
workshop, bounce around ideas, and then
consolidate the thinking into a document. We
had a lot of good feedback—in some cases
probably 100 individual contributions to the
Straw Man documents. We would then develop
a Tin Man document for each of the programs
and work through those, to ultimately lead into
the business plan for the project. It matured the
thinking of the project quite quickly, and it
didn’t feel like an invention being planted on the
community from outside. This was something
the community built itself.
‒ Dr Markus Buchhorn
Research Data Manager, RDSI Project

16|
NodeDevelopment
The NoDe Development programme was
designed to identify, strengthen and develop
research data centres so that they were able to
hold and process high data volumes. These data
centres became Nodes of the RDSI project, and
their operators were provided with
establishment funding from this programme.
The Node Development programme funded
the development of eight high capacity Nodes:
six Primary Nodes located in Brisbane, Sydney,
Canberra, Melbourne, Adelaide and Perth, with
two additional Nodes inTownsville and Hobart.

17|
IdentifyingtheNodes
RDSI went through a process of calling for
proposals. We were all looking at what our
individual contribution to the national
infrastructure would be, and I remember in
Queensland we focused on life sciences and eco
sciences as being the main areas where we
thought that there was a really significant body
of research expertise.
‒ Rob Cook
CEO, QCIF

18|
Respondingtothecall
forNodes
We put a proposal to our members that
Intersect propose to become a Node of RDSI.
Intersect has twelve university members, quite a
lot, and the thing that is interesting is that all
twelve quickly said, ‘Yes, this is a really good
idea.’ So we responded to the call for proposals
and we were one of the Nodes selected from the
country.
‒ Dr Ian Gibson
CEO, Intersect Australia

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RDSIfundedNodes
January
February
March
April
May
June
July
August
September
October
November
December
22/03/2012
5/04/2012
21/05/2012
25/06/2012
5/07/2012
10/07/2012
4/09/2012
2/11/2012

Thedata
collections
Chapter III

21|
ResearchDataServices
The ReDS programme was designed to identify
research data holdings of lasting value and
importance and contribute funding to their
development at the most appropriate Node.
ReDS delivers storage services in support of
significant data collections, research data sets
and associated access tools which are
aggregated into related holdings that add value
to each other through co-location.

22|
Selectingcollections
The value of data is only realised when it’s used,
so having data that is going to be reused was a
critical part of whether it could be stored
through the ReDS program. Every collection
that has been given an allocation through the
ReDS program meets certain criteria that
indicate or demonstrate its national significance.
‒ Peter Hicks
ReDS Program Manager, RDSI Project

23|
Meritcriteria
Determining criteria by which research data
might be assessed for merit was difficult across
disciplines. You could assess a collection based on
how many people it would be shared with. But
what might be an appropriate audience size for
sharing climate data would not be the same for
sharing medical data or humanities data. It was
very challenging to find merit criteria that
would carry the same weight across all
disciplines.
‒ Dr Frankie Stevens

24|
Datastorageisa
commitment
Many of the Nodes had experience with merit
allocation processes used for high performance
computing. But with HPC, the resources are
used, and at the end of the cycle the whole
process is repeated. When you try to think about
that for data, for long-term storage, you’re not
thinking about a resource that goes away in six
months. You’re making a long-term
commitment. And so the assessment of merit
was a much bigger challenge.
‒ Dr Markus Buchhorn

25|
Identifyingcollections
The Intersect model is we have staff located on
campus with our member universities, a team of
roughly 15 people already talking to research
groups, telling them about options and services
available to them. So that team were now
looking for collections that might benefit from
being on the RDSI infrastructure.
‒ Dr Ian Gibson

26|
Exposingscience
agencycollections
At NCI we’ve worked very closely with the
science agencies we are associated with—CSIRO,
Geoscience Australia, and the Bureau of
Meteorology—to expose the national and
international collections that have been locked
up inside those agencies. And the win-win is
that the exposure to the national community is
of value because these collections otherwise
would not have been available, and the
confluence of them enables transdisciplinary
research. The advantage to the agencies is that
the availability of the copy here puts that data
in a rich computational environment, much
richer than they have internally. That’s the
nature of the win-win that’s been possible.
‒ Prof Lindsay Botten
Director, National Computational Infrastructure

27|
Thelongtailof
researchdata
Coordinated research groups like astronomers
are able to collect their data and curate it, and
eventually they will find the storage. But the
humanities, medicine, the environmental
sciences, they were less united in their purpose,
and I always saw RDSI as a vehicle for bringing
those people together and providing them the
nascent infrastructure to store their data and
make it available.
‒ John Shipp
RDSI Board

28|
DataatRDSINodes
Last updated 14/12/2014
Click graph for current figures

29|
55Petabytesofdata
availableinover70
Petabytesofstorage
That these are huge numbers is beyond question;
perhaps more astonishing is that this is an order
of magnitude increase in just 4 years.
Even more encouraging is that this data is
spread across every one of the 22 research
disciplines. From Humanities to Radio
Astronomy, no Field of Research has been left
untouched.

30|
CollectionsbyFieldof
Research Last updated 14/12/2014
Click graph for current figures

31|
Aboutlargeallocations
The RDSI project allocated up to $9.4M of funds to
support large collections at Nodes. Nodes were given
the opportunity to submit funding proposals for
collections that were too large to be funded under the
initial ReDS agreement. Large collection proposals
were evaluated by the RDSI Project Board who
decided a total of 5 proposals will be funded.

32|
Largeallocations
I’m really pleased about the large allocations.
Having that strategic view at the research
community level of how storage is used to
aggregate data from particular domains in a
way that enables advanced research, is a critical
outcome of the ReDS programme.
‒ Peter Hicks
ReDS Programme Manager, RDSI Project

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Anationalmedical
researchdatastorage
facility
Recognising that there was a potential need to
support health and medical research data
collections, we put in a proposal to establish a
national medical data storage facility using
funds from the ReDS special allocation process.
We put that proposal to the medical research
community and we were overwhelmed with
responses. Forty-seven institutions around
Australia nominated major collections they
would like to store. So what we have now is an
opportunity to build a national medical research
data storage facility. This is something that is
quite uncommon globally. It will allow
researchers to get the serendipitous second use
outcomes and impacts from that data.
‒ Dr Ian Gibson

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Thelargeallocations Murchison Widefield Array Data Archive: The Murchison Widefield
Array (MWA) project is funded for operations over a two-year period,
which commenced in July 2013. These data sets, of international
importance, will assist a global Astronomy and Astrophysics
community to do research into the main science goals of the MWA,
which include: exploration of the early Universe and the search for
signals from the first stars and galaxies; exploration of the transient
and dynamic Universe; studies of the Earth's ionosphere; and the study
of astrophysics related to objects in our galaxy and in the distant
galaxies.
Participating RDSI Node is iVEC.
National Environmental Research Data Centre: The National
Environmental Research Data Collection (NERDC) comprises
international and national reference collections spanning five fields.
This multidisciplinary confluence of collections: (a) spans the
lithosphere, crust, biosphere, hydrosphere, troposphere, and the
stratosphere; (b) encapsulates the complex interactions within, and
amongst, these layers, and (c) will enable new, transdisciplinary
approaches to research.
Participating RDSI Node is NCI.
National Genomics Data Storage Facility: Genomics is a critical and
complex science for the understanding of living forms and the way
they are impacted by the environment, for improving medicine, and
understanding food amongst many other uses. The facility will store
and make available large volumes of genome data generated at the
leading national centres, as well as essential national and
international genome libraries.
Participating RDSI Nodes are Intersect, VicNode and QCIF.
Australian Coordinated Characterisation Data Space: The ACCDS
underpins national-scale research programs, in particular two
recently established characterisation-intensive ARC Centres of
Excellence: the ARC Centre of Excellence in Advanced Molecular
Imaging (CAMI), which will develop innovative imaging
technologies to explore the immune system; and the ARC Centre of
Excellence for Integrative Brain Function (CIBF), which is tackling
the challenging problems involved in understanding how the human
brain works.
Participating RDSI Nodes are VicNode, Intersect and QCIF.
Australian National Medical Research Data Storage Facility: The
foundation data sets for this collection represent major national
assets supporting research into Australia’s most significant diseases
including heart disease, mental illness, the major cancers, as well as
the increasing problems of lifestyle diseases such as diabetes and
obesity. Importantly, children’s health and the health of our aging
population are both well supported in the foundation data sets of
the ANMRDSF.
Participating RDSI Nodes are Intersect, VicNode and QCIF.

Anintegrated
infrastructure
Chapter IV

36|
DataSharing
Programme
The DaSh programme was designed to develop
the DaSh Collaboration Network (DaShNet)
and the DaSh Technical Architecture. The
integration of these two major parts of the
DaSh programme became the DaSh Technical
Framework, which describes the network, data
movement capabilities, security and identity
matters, data access, cloud gateway access,
test platform for the programme’s components
and workflow automation capabilities for the
RDSI-funded Nodes.

37|
Whyisithard?
Why is it hard, relative to other programs? It’s
hard because data has a narrative that’s
different for every data stream. Every data-
oriented organisation thinks their data is special
and different from everybody else’s. Really it
should be about revealing data, gathering it
together, and developing tools to express and
analyse it.
TPAC Director and Professor of Physical Oceanography

38|
Buildingtechnicalskills
acrossthesector
One of the things the project has been able to
do is to fund technical and data specialists at
the Nodes. Many of the techniques and skills for
storing, moving, and accessing large sets of data
were new to the project and to the Nodes. Being
able to invest in building up a community of
people in the sector with these skills and
capabilities has been one of the important
contributions of RDSI.
‒ Viviani Paz
RDSI Project Manager

40|
Theneedforafast
network
One of the significant technical challenges to
consider was moving data. We experienced this
early in the project as the ARCS Data Fabric
drew to a close and people were trying to move
the Integrated Marine Observing System data
from Perth to Hobart and Brisbane. The data
was going at the speed of congealed porridge
running down a hill. It was clear that the
network capabilities—not just fast networks, but
the techniques, the tools, the software for using
them—weren’t in place. So the Project has
solved a very serious challenge. When AARNet
put in the data transfer network, they are now
certifying that they’re getting 95 percent use of
the capacity of a 10-gigabit link. That is
enormous compared with what was there. It’s
not just the bandwidth that’s changed.
‒ Dr Nick Tate

41|
Thechallengein
movingdata
Without a doubt, the biggest challenge you have
when moving data is that a lot of these datasets
are built upon many files that are inherently
small in nature, and they’re quite difficult to
move over large distances. Even though you
might have a lot of bandwidth available to you,
you can find that 10 terabytes of data can take
weeks if not months to transfer.
‒ Brendan Davey
Deputy Director, TPAC

42|
Network
enhancements,
AARNetandNRN
Our goal was to ensure we could get multiple
10 gigabits of capacity into the RDSI sites. We
were looking to get every Node connected to the
AARNet backbone with capacity significantly
over and above what a big university would
have, so they could provide services to a
community. And to do that we needed to
ensure there were redundant fibre paths, and
the appropriate network infrastructure on those
fibres to deliver that capacity.
‒ Peter Elford
Network Program Manager (2013), RDSI Project

43|
ConnectingNodesto
Nodes,andNodesto
Researchers
The Data Sharing Network (DaShNet) is a reliable high-speed network
service built over the new AARNet4 backbone network. It connects
RDSI-funded Nodes to each other and researchers around Australia. It
can ultimately support up to 100 gigabits per second, significantly
increasing data transfer rates across the country.

45|
Makingiteasytofind
andaccessdata
Mediaflux will enable the research community to
have useful data management tools that are
consistent across Australia, so that people will be
interacting with research data in the same way,
irrespective of where they’re located.

47|
Identityandaccess
management
In Australia we already had the Australian
Access Federation, a trust fabric for identity
management. But one of the things that became
very plain early on is that although it handles
web access for everyone, it can’t yet do access
via other methodologies. This is where the
project got into territory where we were cutting
new ground.
‒ Richard Northam
Node Development Manager, RDSI Project

49|
Securingthedata
One of the toughest parts of looking at the
security models for this project was to
understand how the Nodes would collaborate
and share responsibility for the data and data
transfers. How they would manage the
relationships with researchers to give them a
level of comfort that the integrity of their data
is being maintained. When your research data
has been under your direct control and then it
goes outside your own perimeter, there’s a
concern that you don’t know what’s happening
with it. So for me, it’s been a management job
of perception more than anything else.
‒ Mark McPherson
RDSI Security Policy Manager

50|
Willmydatabesafe?
One of our biggest challenges in getting people
on board is to assure them that their data is
going to be safe, it’s going to be secure, that
they’ll have access to it, and their partners who
use the data will have access to it.
‒ Brendan Davey

51|
Removingthe
obstacles
We were initially concerned about whether
researchers would adopt a central data storage
facility at all. We drew up a list of 10 obstacles,
and you could be pretty sure that if you started
talking to a researcher about putting their data
on RDSI, they’d start going through these 10
obstacles one by one without you prompting
them. ‘I can’t touch it anymore, it’s insecure,
you’re only here until the end of 2014, I might
have to pay for it,’ and so on. One by one we’ve
been able to make these obstacles insignificant.
‒ Rob Cook
CEO, QCIF

53|
Connectingwith
computefacilities
The Raijin supercomputer at NCI
“Data is a vital enabler of research.
Big data can only be handled in a
rich computational environment. It’s
not the data alone. It’s not the
compute alone. It’s the confluence of
the two. People advance their
research by being able to have well-
managed, integrated collections of
data where they can explore new
ideas by having a confluence of
different datasets available to them.”
Director, National Computational
Infrastructure

55|
VendorPanel
TheVendor Panel programme, implemented in partnership with the
Council of Australian University Directors of InformationTechnology
(CAUDIT), was created to facilitate the procurement of storage
related infrastructure, software and services.The purposes for the
programme were twofold. Firstly to allow Nodes, universities and
other authorised users to avoid lengthy tendering processes by
using an appropriately constructed panel, and secondly to support
volume pricing across Nodes and the wider Higher Education and
Research Sector.

56|
Anopenmindtowards
solutions
In many of the research infrastructure projects
we’ve seen before, there has been a focus on
adopting only open source solutions or solutions
developed by other researchers. We took the
view that we should go with a completely open
mind to the process. You can use commercial or
open source or other not-for-profit
infrastructure software. It doesn’t matter. The
important thing is to pick the best that’s
available at the time and to make sure it’s
affordable, and that’s why we’ve been
negotiating collectively. For example, the
software we’re using in our data transfer
network is a commercial product and by
negotiating effectively, we’ve been able to
acquire it at a price that allows the sector to do
things which have not been possible in the past.
With the Vendor Panel transferring to CAUDIT
over the coming months, this is a legacy for the
sector as a whole.
‒ Dr Nick Tate

57|
VendorsonthePanel
Twenty-twoandcounting
Last updated 14/12/2014
Click image for current members

58|
SavingMoneyforthe
Sector
CIOs have challenges in navigating procurement
for IT services, testing the market, keeping up
with suppliers. The Vendor Panel simplified
storage options for the whole sector and was a
catalyst for CIOs to open a dialogue with the
research community. It took data storage down
from being too complicated, too hard, to being
a commodity product you can buy and use as
you need. Probably we won’t realise the benefits
for a few years, but it saved the sector an
enormous amount of money.
‒ Peter Nikoletatos
RDSI Project Board

59|
Towardspubliccloud
This is potentially the last generation of serious
storage the Nodes will own. The project has
looked extensively at how public cloud could
complement in-house storage and compute, and
we’ve established agreements with Amazon Web
Services to eliminate costs in moving research
data in and out of the public cloud, to enable
the Nodes to make some informed decisions
about that in the future.
‒ Paul Campbell
Vendor Engagement Specialist, RDSI Project

60|
Adatastorage
ecosystem
When it comes to large-scale infrastructure,
organisations for the foreseeable future will use a
hybrid solution. They will have some capability
internally, some from private cloud providers
such as Intersect, and some from public cloud
infrastructure. We are part of an ecosystem that
allows the data to flow around these different
parties which collectively provide an ongoing
solution to data storage.
‒ Dr Ian Gibson

Chapter X
From July 2013, the RDSI Project began collecting use cases on how
research groups across Australia are using collections stored at RDSI
nodes, and why RDSI-funded storage is important to their research.
From high energy physics to the humanities, from climate to cancer
research, researchers are discovering common needs around research
data.They all need to preserve and store their data, access and share it
with collaborators, bring disparate collections together to be analysed
by common tools, and in many cases, reuse data that was collected by
someone else or for a different purpose.
CaseStudies

62|
Amajornewhuman
genomecollection
How RDSI is helping:
The sequencing will generate 4.5 petabytes
of data over the next 3 years. Storage
through RDSI helps reduce costs to
researchers and allows the data to be
moved easily among Nodes for analysis.
The outcome:
Australian researchers are positioned to
take a leading role in emerging genomics
research through access to cost-effective
genome sequencing and genomic
collections of international importance.
The challenge:
The Garvan Institute of Medical Research is
sequencing over 4000 healthy human
genomes to create a Medical Genomics
Reference Bank for researchers around the
world.
Image courtesy of P. Morris, Garvan Institute
“We see this as providing Australia with a seat at the
table and an opportunity to be amongst the world
leaders in an area that’s emerging so rapidly.”
– A/Prof Marcel Dinger
Head of Clinical Genomics and Genome Informatics, Garvan Institute

63|
Accesstowhatwas
onceinaccessible
Through RDSI storage, Richard is now able
for the first time to make this collection of
over 1 petabyte of data accessible and
searchable by researchers everywhere.
The outcome:
The footage is being used by the
Queensland Government to track turtle
hatchling success rates at Raine Island and
by JCU to study the ecology and biology of
venomous box jellyfish.
The challenge:
Award-winning natural history
cinematographer and marine scientist
Richard Fitzpatrick has 20 years worth of
film footage of the complex behaviours of
ocean and terrestrial creatures.
“The fact that it’s now searchable is
just huge. There are 5000 hours of
footage, and now you can go in and
chase stuff yourself. That in itself is
monumental.”
– A/Prof Jamie Seymour
Director, Tropical Australian Venom
Research Unit

64|
Openingthedoorto
uselargedatasetsina
HPCenvironment
RDSI storage makes available data that was
previously locked within agencies. RDSI
storage within the NCI computational
environment opens the door for using HPC
to work with these large datasets.
The outcome:
The National Flood Risk Information Project
(NFRIP) is using the Data Cube to create a
portal showing areas of land where surface
water has been observed from satellites in
the past, to raise community awareness of
flood risks.
The challenge:
Geoscience Australia is bringing together 30
years of earth observation satellite images
into a Data Cube that creates a geographic
time machine, allowing scientists to apply
the data to big problems such as managing
flood and fire risk.
“We now have hundreds of terabytes of satellite data
covering all of Australia going back 30 years, and we
wanted to begin applying it to big problems.”
‒ Dr Adam Lewis
National Earth & Marine Observations Group, Geoscience Australia

65|
Preservingcollections
A growing number of these collections have
been brought together by the human
communication science community, stored
through RDSI, and are now accessible
through the Alveo virtual laboratory, funded
by NeCTAR.
The outcome:
These collections are being preserved and
used in new ways by linguists, psychologists,
musicologists, and computational scientists.
The challenge:
Collections containing real examples of the
use of speech, language, and music were
stored in locations disparate from one
another. Accessibility was difficult, and
some collections were at risk of being lost.

66|
End-to-endresearch
datamanagement
The challenge:
The Australian Synchrotron needed to
protect, store, provide access to, and allow
researchers to share, reuse, and validate
data from Synchrotron beamline
experiments.
Technical staff from the Monash eResearch
Centre and VicNode worked with the
Synchrotron to develop a solution, which
uses RDSI storage to store and provide
access to the data. It also uses the NeCTAR
Research Cloud and DOIs from ANDS.
The outcome:
Store.Synchrotron is the first persistent,
open data store in the world for a
synchrotron. Thousands of datasets have
been stored in the permanent, accessible
archive.
“Ours is going to be the only system in the world where
all of the primary data from the beamlines, every frame,
will go into the store. And it will be there. This is an
absolute world first.”
‒ Dr Tom Caradoc-Davies
Principal Scientist for Macromolecular Crystallography, Australian
Synchrotron

67|
Datareuseandnew
collaborations
RDSI storage integrated with the NeCTAR
Research Cloud allows these models to be
available and easily run by other
researchers. As a result, use of the models
by other groups is growing rapidly.
The outcome:
A group of National Resource Management
Regions (NRMs) has found them so
beneficial they are funding Dr VanDerWal’s
group to include fresh water species
information.
The challenge:
Dr Jeremy VanDerWal at JCU creates
models to study how climate change will
affect bird and animal populations. The
models were previously behind university
firewalls. Providing access to others was
difficult.
“Previously my thinking was limited by the small amount
of storage and computing that was available to me. I
always had to summarise down and minimise the data. I
don’t have to do that now. I don’t have to worry about
the live disk limitation or the compute resources. Now I
can keep doing the research as I’d like to see it done.”
‒ Dr Jeremy VanDerWal
Centre for Tropical Biodiversity and Climate Change, James Cook
University

Lookingbackand
lookingahead
Chapter XI

69|
ProjectSuccess
The RDSI Project set out to transform the way
in which research data in Australia is stored and
made available to its potential users. By any
measure, the project has been successful in
achieving this.
When the contract for the project was signed
between the University of Queensland and the
Commonwealth Government on Christmas Eve
2010, it has been estimated that there was a
total of about 5 Petabytes of research data
stored throughout the sector and that much of
this was inaccessible to most researchers. By the
end of the project in 2015, it is expected that
over 55 Petabytes of data will be available in
over 70 Petabytes of storage. Even more
importantly, this will be stored in facilities that
are able to make it collaboratively available to
researchers.
‒ Dr Nick Tate

70|
Areresearchersfinding
itvaluable?
Researchers are voting with their data. They’re
bringing it to the Nodes, they’re putting it on.
It’s a great leap forward.
‒ Peter Elford
Director, Government Relations, AARNet

71|
Culturalchange
‒ In addition to putting the tin on the ground
to store data, a key success of the RDSI
Project has been to facilitate cultural change
around collaboration and sharing.
‒ Brian Anker
Chair, RDSI Project Board

72|
Supportingresearch
activities
Coming from an IT background, I learned so
much from working on this project about
supporting research activities in the next decade.
It’s not just about compute and store, it’s about
collaboration. It’s about connecting, about
access, about identity. It’s about protecting the
work. It’s about curation of data. It’s about
making it available for groups, not just for now
but in the future. It’s just so big, it takes a while
to get your head around it.
‒ Peter Nikoletatos
RDSI Project Board

73|
Fingersintothefuture
With a lot of projects there is a start, a finish,
and you move onto the next thing. This thing
really has fingers into the future in being able to
act as a building block for other initiatives to
build on.
‒ Brian Anker
Chair, RDSI Project Board

74|
Dataaccess
Our views of data have changed as RDSI has evolved.
When the project started, everyone was talking about
data storage. But as you start storing the data, you
realise the real problem is access. In the early days, the
access mechanisms available were extremely primitive.
Now we have the data stored, we have the Mediaflux tool
to make data easy to find and access, we have Aspera
for moving large quantities of data. These weren’t even
really imagined when we started the RDSI project. As we
go forward, people will begin to realise that the real
value that’s been delivered by the system is the
organisation of the data into a way that people can find
it, access it, and manage it. That’s a big change that
RDSI has made.
‒ Rob Cook
CEO, QCIF

75|
Thinkingoutsidethe
box
A lot of people say to me, ‘This is great. I can
now go to one location, I can have access to this
dataset and to this other dataset right
alongside, whereas before I’d have to go to
multiple locations to get all the data I needed.’
And what I’m hearing in the wider research
community is that people are starting to think
outside the box. They can now suddenly combine
two datasets from different disciplines together
and potentially do new science. So it’s quite
exciting.
‒ Brendan Davey

76|
Focusonresearch
Once you’ve solved the problem of knowing how
to move data around and knowing where to put
it, you can start to focus on other things. And
that’s really where RDSI will continue to change
research in Victoria. You won’t need to focus on
where to put the data and whether or not it’s a
good idea to put it there. You can move on. As
an operator, the best thing is when you do get
people to use these services and they never, ever
call you again. Because it means the service is
humming away.
‒ Dr Steven Manos
Manager Research Services in ITS, The University of
Melbourne

77|
Thevalueofdata
Researchers are beginning to realise the value of
their data. A professor in pathology from The
University of Melbourne was one of our first
major consumers of data storage. We had gone
in to speak to her. Their archiving solution was a
set of hard drives on a shelf, and she wanted
advice on a better solution. She said, ‘Well, I pay
$70,000 a year in liquid nitrogen to preserve
my physical tissue samples. Why wouldn’t I pay
the equivalent to look after my digital assets?’
For her, the value proposition was obvious.
‒ Dr Steven Manos
Manager Research Services in ITS, The University of
Melbourne

78|
Amillion-foldincrease
inscale
In 1996 I became the Chairman of the World
Ocean Circulation Experiment Data Products
Committee, which was all about assembling the
data from this billion dollar international
project. I had 12 organisations working for me
and in those 12, probably 35 effective full-time
staff delivering up data on a regular basis. To
give you a sense of the scale, the final product in
2002 from this billion dollar experiment fit
onto a single DVD. It was just 4.7 gigabytes, but
we won accolades because that dataset, huge at
the time, was delivered across the Internet.
Now in 2014, we have over 30 petabytes of
data approved for ingestion into the RDSI Nodes
across Australia. So that’s nearly than a million-
fold increase in data, with fewer people
involved, and with the additional challenge that
the datasets come from a much more diverse
research community.
Director of TPAC and Professor of Physical Oceanography

79|
Puttinginachairlift
Sharing research data for everyone’s benefit
involves taking a risk. You have to climb a hill.
With the RDSI investment, the government has
put in a chair lift to help the research sector get
up the hill to see the benefit on the other side.
‒ Prof Liz Sonenberg
RDSI Project Board

80|
Movingoutofthedata
iceage
An interesting lesson that wasn’t clear to me
when we started is that we’re really at a very
early stage of maturity in dealing with data. We
didn’t realise that we were in the ice age; it was
all frozen. You can get a real sense of excitement
from recognising what people will be able to do
with data when it becomes so easy to use. And
it will, you know.
‒ Rob Cook
CEO, QCIF

81|
Evolution
I think the RDSI Project has taken us through a
significant learning curve. Data is a tricky thing.
It’s so multi-dimensional, and it has so many
owners. Working with the multiplicity of
interests is quite challenging. And so the place
we’ve ended up is by evolution. You would not
have been able to write it down on a piece of
paper on Day One.
Director, National Computational Infrastructure

82|
Thepathwayisreal
It’s important to understand that it’s not just
about where we have ended up. It’s about the
pathway. The pathway is real.
‒ Dr Rhys Francis
RDSI Project Board

83|
PassingtheBaton
It has been quite a journey over the past 4 years
as together we have created this extraordinary
infrastructure for the research sector. The
project has tackled a rich tapestry issues and
challenges, but with the help of all our
stakeholders we now have a result to be proud
of.
Researchers have made significant gains in the
way they interact with their data by being able
to concentrate on their research rather than
worrying about the volume of data they are
producing or the mechanisms to store that data.
We now pass the baton for continued
development and support of this national
infrastructure to the RDSI Node Operators, who
will lead the next step in its evolution. We wish
them luck and long lasting sustainability.
‒ Dr Nick Tate

85|
ProjectOffice Communications
Project Director
Dr Nick Tate
n.tate@rdsi.uq.edu.au
+61 7 3365 2019 | +61 412 674 010
Communications Officer
Asher Vennell
a.vennell@rdsi.uq.edu.au
+61 408 517 376
Project Manager
Viviani Paz
v.paz@rdsi.uq.edu.au
+61 7 3365 2033 | +61 402 280 257
Storyteller
Patricia McMillan
patricia@patriciamcmillan.com
+61 434 602 050
Office Manager
Toni Walkinshaw office@rdsi.uq.edu.au
+61 7 3365 2030 | +61 419 477 490
Solutions Specialist
Loretta Davis
loretta.davis@rdsi.uq.edu.au
+61 407 370 474

86|
DataSharing(DaSh)
Vendor Engagement Specialist
Paul Campbell
paul.campbell@cogentia.com.au
+61 7 3878 2666 | +61 402 002 266
Security Policy Manager
Mark McPherson
mark.mcpherson@rdsi.uq.edu.au
+61 418 425 872
NodeDevelopment(NoDe)
NoDe Manager
Richard Northam
richard.northam@rdsi.uq.edu.au
+61 417 044 625
ResearchDataServices(ReDS)
ReDS Programme Manager
Peter Hicks
peter.hicks@rdsi.uq.edu.au
+61 401 103 640
Research Data Manager
Dr Markus Buchhorn
Markus.buchhorn@rdsi.uq.edu.au
+61 417 281 429
Research Data Manager
Dr Frankie Stevens
frankie.stevens@rdsi.uq.edu.au
+61 435 657 730

87|
Interactingwiththe
community
I’ve really enjoyed the breadth of interaction
we’ve been able to have as a project team across
the stakeholders– the research communities, the
universities and science agencies, the Nodes. It’s
been wonderful to be able to talk to all of those
stakeholder groups. One of the things that’s been
most interesting for me has been to see the
different approaches those groups bring to
data—how research data management might be
viewed at the institutional level, versus the state
level, versus a person working in a laboratory.

BoardMembers
Brian Anker
 Independent Chair
Dr Rhys Francis
 Director - eResearch Futures P/L
Professor Doug McEachern
 Former ProVice Chancellor Research and Innovation -
The University ofWestern Australia
Professor Anton Middelberg
 DeputyVice Chancellor (Research) -The University of
Queensland
FormerBoardMembers
Peter Nikoletatos
 Executive Director and Chief Information Officer - La Trobe University
John Shipp
 Vice-President - Australian Library and Information Association
Professor Liz Sonenberg
 Pro Vice-Chancellor (Research Collaboration) - The University of Melbourne
Professor Max Lu
 Provost and Senior Vice-President - The University of
Queensland
Professor Jill Trewhella
 Deputy Vice-Chancellor (Research) - The University of
Sydney

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