Tomorrows researchers

19/12/2014 Digital Future of Research. Manchester Metropolitan University. slide 1
Tomorrow's Researchers
Matthew Dovey
Programmes Director, Jisc
Skills Needed to Adapt to the Future Demands of Digital Research

“Research Technologists”

http://www.jisc.ac.uk/publications/briefingpapers/2011/bpsupportingresearchers.aspx

CSC, SURF, Jisc report to EU e-IPF
 Recognition of the need for Research Technologists and the organisational
and financial consequences is crucial to the impact of research.
 Advocacy - It is crucial to influence policy and resource allocation of both
the research funders and also the institutions undertaking research in
order to establish this role.
 Training - Incorporating a basic level of understanding and training is
critical – this should happen for all researchers and be introduced at the
point at which they are first exposed to research. Training on the use and
impact of technology on the research process should therefore be included
from undergraduate level and fully integrated into research student
programmes.
 Embedding - With an established career pathway and appropriate training
it will be necessary to incorporate and empower the Research Technologist
in the research process.
19/12/2014 slide 6

Institutional
and funding
council
structures and
policies
ICT facilities
and associated
support
Training
researchers
Transforming
or making
available
research
outputs
Creating
technology
Creating
innovation
Developing
software
Using tools and
e-infrastructure
Data curation
and
management
Services and
solutions
RESEARCH
“Skills Wheel”
19/12/2014 Digital Future of Research. Manchester Metropolitan University. 7

Institutional
and funding
council
structures and
policies
ICT facilities
and associated
support
Training
researchers
Transforming
or making
available
research
outputs
Creating
technology
Creating
innovation
Developing
software
Using tools and
e-infrastructure
Data curation
and
management
Services and
solutions
RESEARCH
Researcher
“Researcher”

Institutional
and funding
council
structures and
policies
ICT facilities
and associated
support
Training
researchers
Transforming
or making
available
research
outputs
Creating
technology
Creating
innovation
Developing
software
Using tools and
e-infrastructure
Data curation
and
management
Services and
solutions
RESEARCH
ICT Capable
Researcher
“ICT-skilled Researcher”

Institutional
and funding
council
structures and
policies
ICT facilities
and associated
support
Training
researchers
Transforming
or making
available
research
outputs
Creating
technology
Creating
innovation
Developing
software
Using tools and
e-infrastructure
Data curation
and
management
Services and
solutions
RESEARCH
Specialist Support
“IT Support”

Institutional
and funding
council
structures and
policies
ICT facilities
and associated
support
Training
researchers
Transforming
or making
available
research
outputs
Creating
technology
Creating
innovation
Developing
software
Using tools and
e-infrastructure
Data curation
and
management
Services and
solutions
RESEARCH
Research
Technologist
Support &
Knowledge Transfer
“Research Technologist”

Researchers

Digital Roles of the Future Researcher
Information
Manager
Data
Manager
Technologist
PR
Manager
Project
Manager

Information Manager
Information
Manager
Data
Manager
PR
Manager
Project
Manager
Technologist

SCONUL Seven Pillar of Information Literacy
19/12/2014 slide 15Digital Future of Research. Manchester Metropolitan University.

Vitae Framework, Information Literacy Lens: http://www.vitae.ac.uk/researchers/437191/Increasing-the-impact-and-engagement-of-researchers.html

Researchers of Tomorrow Study
 Education for Change, together with The
Research Partnership,was commissioned
by the British Library and JISC to
undertake a groundbreaking study on the
research behaviour of the 'Generation Y'
scholar
 The study spent three years tracking the
information-seeking behaviour of doctoral
students born between 1982 - 1994;
analysed their habits in online and
physical research environments and
assessed how they used library and
information sources, both on and off line
 Over 17,000 doctoral students from more
than 70 higher education institutions
participated in the three annual surveys,
which were complemented by a
longitudinal student cohort study.
 http://explorationforchange.net/index.php/r
ot-home.html

Finding and Using Research Resources
 Text-based and secondary research sources are
predominant, compared to primary sources,
across all subject disciplines and all ages of
student
 Most students found the research information
they sought in more than one kind of resource,
but e-journals dominate
 If they cannot get hold of an e-journal article
almost half the Generation Y doctoral students
make do with the abstract. Fewer older students
are likely to do this
 Only Google commands a similarly important role
as an information source across all subject
disciplines
 Generation Y doctoral students seem rarely to be
aware of the actual publisher or name of the e-
information source, as they rely on their library’s
own interface or Google to locate and access
resources
 There is widespread lack of understanding and
uncertainty about open access and self-archived
resources among doctoral students of all ages

Take-up of Technologies and Applications
 Take-up of most institutionally-provided and open
web technology tools and applications is low
among doctoral students overall
 Generation Y doctoral students are more likely
than older doctoral students to use technology to
assist them in their research
 Generation Y doctoral students tend to use
technology applications and social media in their
research if they augment, and can be easily
absorbed into, existing work practices
 Levels of use of social media and other
applications helpful in retrieving and managing
research information are steadily rising among
Generation Y doctoral students, but those
applications most useful for collaboration and
scholarly communications remain among the least
used
 Fellow students and peers are the major influence
on whether or not Generation Y doctoral students
decide to use a technology application and are
their main source of hands-on help

Collaboration, Sharing and Disseminated Research
 The majority of all Generation Y doctoral students
across all subject disciplines work alone rather than in
collaborative teams
 Informal networking with fellow students and peers is
important to most Generation Y doctoral students in
exchanging information and ideas and warding off the
effects of isolation
 The Generation Y doctoral student’s main place of
work – their institution or home – has an impact on
collaborative and support-seeking behaviours
 The majority of Generation Y doctoral students share
their research outputs only with their work colleagues
 Few doctoral students overall are as yet using
institutional repositories, and concerns exist over, for
example, copyright liabilities if their theses are made
public this way
 With regard to greater openness and sharing in
research, Generation Y doctoral students tend to
reflect a mixture of in-principle endorsement and the
inclination to retain control over their own work, which
characterises academic researchers and wider
scholarly communications in general

Institutional Services and Facilities to Support Research
 While the majority of Generation Y doctoral
students take up some training in finding and
using secondary source research resources, they
are less likely to opt for training in using
technology-based methods and tools, such as e-
research infrastructure or Web 2.0 applications
 Among institutional training offers there is
widespread and heavy reliance on ‘traditional’
modes of training delivery, such as lectures, talks
or demonstrations, and workshops. Face-to-face
methods are favoured by students over online
delivery
 Working mainly from an institutional base has
positive implications for networking and support
among peers and academics, but home-based
Generation Y doctoral students may be more
likely to make use of the support services
provided by the institution
 The high importance assigned by Generation Y
doctoral students to some institutional services
and facilities is not matched by equally high levels
of satisfaction with the services and facilities on
offer in their institutions

Key Findings
 Doctoral students are increasingly reliant on secondary research resources (e.g. journal
articles, books), moving away from primary materials (e.g. primary archival material and large
datasets).
 Access to relevant resources is a major constraint for doctoral students’ progress.
Authentication access and licence limitations to subscription-based resources, such as e-
journals, are particularly problematic.
 Open access and copyright appear to be a source of confusion for Generation Y doctoral
students, rather than encouraging innovation and collaborative research.
 This generation of doctoral students operate in an environment where their research
behaviour does not use the full potential of innovative technology.
 Doctoral students are insufficiently trained or informed to be able to fully embrace the latest
opportunities in the digital information environment.
 Key Barriers
– Time Constraints - finding electronic research and getting hold of relevant resources
– Doctoral students believe that they are insufficiently trained or informed to enable them to
embrace the latest opportunities
– Low awareness and understanding of intellectual property and copyright and open access

Data Manager
Information
Manager
Data
Manager
Technologist
PR
Manager
Project
Manager

Royal Society
Science as an Open Enterprise Report, 2012
19/12/2014 slide 25
• ‘how the conduct and communication of
science needs to adapt to this new era of
information technology’.
• ‘As a first step towards this intelligent
openness, data that underpin a journal
article should be made concurrently
available in an accessible database. We are
now on the brink of an achievable aim: for
all science literature to be online, for all of
the data to be online and for the two to be
interoperable.’
• Royal Society June 2012, Science as an
Open Enterprise,
http://royalsociety.org/policy/projects/scienc
e-public-enterprise/report/
Digital Future of Research. Manchester Metropolitan University.

G8 Science Ministers Statement London UK, 12 June 2013
Open Scientific Research Data
• To the greatest extent and with the fewest constraints possible publicly
funded scientific research data should be open, while at the same time
respecting concerns in relation to privacy, safety, security and commercial
interests, whilst acknowledging the legitimate concerns of private partners.
• Open scientific research data should be easily discoverable, accessible,
assessable, intelligible, useable, and wherever possible interoperable to
specific quality standards.
• To maximise the value that can be realised from data, the mechanisms for
delivering open scientific research data should be efficient and cost
effective, and consistent with the potential benefits.
• To ensure successful adoption by scientific communities, open scientific
research data principles will need to be underpinned by an appropriate
policy environment, including recognition of researchers fulfilling these
principles, and appropriate digital infrastructure.

19/12/2014 slide 27
Data as New Output of Research
‘technology has enabled data to become the prevalent material and currency
of research. Data, not information, not publications, is rapidly becoming the
accepted deliverable of research.’
Graham Pryor, Observations on the RLUK Reskilling for Research Report
http://www.dpconline.org/newsroom/whats-new/842-whats-new-issue-44-
april-2012

19/12/2014 slide 28
Changing Research Methods and Requirments
• Wide variety of research practices in sub-
disciplines.
• Unequal distribution of generic information
skills.
• Importance of generic and bespoke data
analysis tools; importance of programming
skills.
• ‘New technologies for sharing data and
for combining data from disparate
sources are particularly valuable in
multidisciplinary fields such as earth science
and nanoscience. ... The challenge of
federating, mining, analysing and
interpreting these data will be a key focus
in coming years.’
http://www.rin.ac.uk/our-
work/using-and-accessing-
information-resources/physical-
sciences-case-studies-use-and-
discovery-

19/12/2014 slide 29
“Its not just curation, retrieving and
integrating data – its also what we do with it!”
Jim Gray, Microsoft
“When you go and look at what scientists are doing, day in and day
out, in terms of data analysis, it is truly dreadful. We are embarrassed
by our data!”
So what are the priorities?
1. Ensuring scientifically valid processing
2. Innovative manipulation to create new information
3. Effective management of research data
There is a serious issue of education, training and support at
undergraduate, doctoral and post-doctoral levels
Geoffrey Boulton (University of Edinburgh)

Big Data

Why Research Data Management?
• Research Excellence & Impact – data will be cited; used by
others including peers, other disciplines, the public, industry,
in learning – ability to meet global challenges; innovate &
create new research areas.
• Research integrity - replication, verification of research,
improvement of methods & results.
• Efficiency - save duplication of research effort, data creation
& therefore costs; ease of access & re-use.
• Managing risks – ability to meet FOI requests; protect
reputation.

The reality …
Social Scientist- “I have
notes, photos & video and
audio of subjects it would
take way too long to
anonymise it ”
Informatics researcher-
“ yes I will share my
data but people should
register; & why change
to the Open Data
Commons licence I
have a bespoke licence
I have always used”
Philosopher- “I
don’t have data, I
annotate books”
Bio-scientist- “why
would I put my data in
a repository? I share it
informally with my
peers, no-one else
would understand it. “
Engineer “ I
have lots of data
but you need a
licence to this
bespoke software
to use it”

DUDs
The data centre
under the desk (or
in a back pack) is
not adequate.

19/12/2014 slide 34
Evidence that significant data loss occurs
 ‘Departments typically don’t have guidelines or norms for personal back-
up and researcher procedure, knowledge and diligence varies
tremendously. Many have experienced moderate to catastrophic data
loss.’
– Incremental Project Scoping Study and Implementation Plan
http://www.lib.cam.ac.uk/preservation/incremental/documents/Incremental_Scoping_Report_170910.pdf
 ‘The current environment is such that responsibility for good data
management is devolved to individual researchers and in practice PIs set
the 'rules' and establish the cultural practices of the research groups and
this means there is good data management practice going on in pockets
but no consistency across groups. There is also consequently a high
risk of data losses by a number of means’.
– MaDAM Project Requirements Analysis
http://www.merc.ac.uk/sites/default/files/MaDAM_Requirements%20_%20gap%20analysis-v1.4-
FINAL.pdf
UHMLG: Innovation, Transformation, Continuation - Bristol

JISC Research Data Management Programme

Improved
RDM
skills
Improved
DM
planning
Improved metadata
Improved
storage
decisions
Improved
access control
Improved
institutional
support for RDM
Etc.
Greater
visibility / use
of institution
research data
Improved
compliance with
funder
requirements
Time / costs
saved by
improved
RDM
infrastructure
Improved use /
uptake of RDM
infrastructure
Raised
understanding and
awareness
of RDM
Higher profile for
researchers
Improved metrics
for REF etc.
Institutional
reputation
enhancement
Higher bidding
success rate
Improved
productivity /
effectiveness
Minimised risk of
data loss
More cohesive
practice across
campus
Improved motivation
for good RDM
practice
Improved
availability of RDM
infrastructure
Enhanced
potential for new
knowledge
creation
Data policy
formation and
compliance
Etc.
Key:
Overall benefit of programme
Benefits addressed by the current evidence-
gathering activity
Potential further benefits of programme activity
Training
attendance
Data policy
promotion
Enhanced
opportunities for
collaboration

Second JISC MRD Programme, 2011-13: http://bit.ly/jiscmrd2011-13
Institutional
RDM
Infrastructure
Services
17 Projects
RDM
Training
5 projects
RDM
Planning
10 projects
Data
Publication
3 projects
Second MRD Programme, 2011-13
Ownership: High level
ownership of the problem,
senior manager on steering
.
Sustainability: Large
institutional contributions.
Develop business cases to
sustain work.
Encouraged to reuse outputs
from first programme and
elsewhere.
Mix of pilot projects and
embedding projects.
Holistic institutional
approach to RDM.

19/12/2014 slide 38
Need for Training in RDM and Data Skills
‘data skills should be made a core academic competency’
‘data handling [should be] embedded in the curriculum’
‘There is a need to go beyond the workshop and the short training course,
and embed preparation for a professional (and personal) lifetime of digital
data curation within the academic curriculum.’
Graham Pryor and Martin Donnelly (2009), ‘Skilling up to do data: whose
role, whose responsibility, whose career? IJDC, Issue 2, Volume 4, pp.158-
170.

19/12/2014 slide 39
JISCMRD Project Findings: Incremental
1. Produce accessible, straightforward
guidance on creating, storing and
managing data.
2. Offer practical training resources with
discipline-specific examples
3. Connect researchers with support staff
for tailored advice and partnering
4. Connect this with a comprehensive data
management infrastructure
Project Page:
http://www.lib.cam.ac.uk/pres
ervation/incremental/index.ht
ml

19/12/2014 slide 40
JISCMRD Training Projects
• Need for subject focussed research data management / curation
training, integrated with PG studies
• Five projects to design and pilot (reusable) discipline-
focussed training units for postgraduate courses:
http://www.jisc.ac.uk/whatwedo/programmes/mrd/rdmtrain.aspx
• Health studies:
http://www.northumbria.ac.uk/sd/academic/ceis/re/isrc/themes/
rmarea/datum/
• Creative arts: http://www.projectcairo.org/
• Archaeology, social anthropology:
http://www.lib.cam.ac.uk/preservation/datatrain/
• Psychological sciences: http://www.dmtpsych.york.ac.uk/
• Social sciences, geographical sciences, clinical psychology:
Project http://bit.ly/RDMantra ; Online course:
http://datalib.edina.ac.uk/mantra/

19/12/2014 slide 41
MANTRA Training Materials, University of Edinburgh
• Online course built using OS Xerte toolkit.
• Sections include:
– DMPs
– Organising Data
– File Formats and Transformation
– Documentation and Metadata
– Storage and Security
– Data Protection
– Preservation, sharing and licensing
• Also software practicals for users of SPSS,
R, ArcGIS, Nvivo
• Research Data MANTRA:
http://datalib.edina.ac.uk/mantra/

19/12/2014 slide 42
DCC How-to Guides
• DCC How-To Guides:
http://www.dcc.ac.uk/resources/
how-guides
– Appraise and select
research data for curation
– How to license research
data
– How to develop a data
management and sharing
plan
– How to cite research data!
• Further Guides in
preparation.

19/12/2014 slide 43
Understanding the challenges of meeting funder requirements:
DMP-ESRC Project
• Led by UK Data Archive: http://www.data-archive.ac.uk/create-manage/projects/jisc-dmp
• Study of data management practices in ESRC funded Centres and Programmes.
• Data Management Recommendations:
http://www.data-archive.ac.uk/media/257765/ukdadatamanagementrecommendations_centresprogrammes.pdf
– Clear roles and responsibilities; RDM coordinator; Data Inventory; Data Management
Resources Library.
– Guidelines on anonymisation, security and backup etc.
– Greater use of collaborative environments; improve usability and training.
• Data Management Costing Tool:
http://www.data-archive.ac.uk/media/257647/ukda_jiscdmcosting.pdf
Projects to understand challenges of meeting funder
requirements: Social Sciences, Engineering, Medical Research, Plant
Microscopy, Gravitational Wave Astronomy, Interdisciplinary:
http://www.jisc.ac.uk/whatwedo/programmes/mrd/rdmp.aspx

19/12/2014 slide 44
Functions of an Institutional RDM Service
1) Requirements
2) Planning
3) Informatics
4) Citation
5) Training
6) Licensing
7) Appraisal
8) Storage
9) Access
10)Impact
• Liz Lyon, ‘The Informatics Transform: Re-Engineering Libraries for the Data Decade’,
International Journal of Digital Curation (2012), 7(1), 126–138;
http://dx.doi.org/10.2218/ijdc.v7i1.220
Institutional Coordination
and Partnerships

Data
Librarians and research managers
have three interlocking suites of
services, to support researcher needs
and institutional policies
Researchers have a cohesive and
interlocking suite of research data
management, publication and
discovery services
Research Data
Management and
Planning Services
Research Data Storage and Archival Services
Research Data
Discovery Services
UKDA,
BADC
Research Data Management Applications
ICSU / WDS
EBI /
GenBank
Research Data Management Applications
Journal Policies Registry
Research Data Registry / Cross
Repository Discovery Service
Key
Established service
Project
Other supported
JISC supported
DMPonline
DMP Registry
Research Data Management and Discovery
Services for the Research Data Lifecycle
SWORD +
Disciplinary Data Repositories
(National and International)
Institutional Data CataloguesInstitutional Data Catalogues
Disciplinary Research Data
Discovery Services
Metadata Exchange Between Journals, Archives,
Repositories
There is a set of
infrastructure
components that
underpin all three
suitesResearcher identifiers Organisation identifiers RegistriesData Identifiers
Data Identifiers and
Metadata Schema
Support for Research Data Lifecycle

data.bris

19/12/2014 slide 48
Consultants in the Scientific Process
• Importance of efforts to share and link data.
• 'The need for librarians to reinvent their roles as
partners in the scientific and research process is
acute.’
• Gives examples of success (library collaborations
in metadata and database development with
chemists).
• Such opportunities ‘where library professionals
become scientific consultants that can advise on
information practices and policies in scientific
collaborations, are one way for libraries to
remain central to the research process.’
• Importance of collaborations across stakeholders:
researchers, librarians, professional societies,
publishers.
http://www.rin.ac.uk/our-
work/using-and-accessing-
information-resources/physical-
sciences-case-studies-use-and-
discovery-

19/12/2014 slide 49
Changing Role for Subject Librarian
A shift can be seen which takes Subject
Librarians into a world beyond
information discovery and management,
collection development and information l
iteracy training, to one in which they
play a much greater part in the
research process and in particular in
the management, curation and
preservation of research data, and in
scholarly communication and the
effective dissemination of research
outputs.
RLUK/Mary Auckland, http://www.rluk.ac.uk/content/re-skilling-research

Technologist
Information
Manager
Data
Manager
Technologist
PR
Manager
Project
Manager

Holistic Research
19/12/2014 slide 52
Result
DataSoftware
Value Transition
'Software is the Modern Language of Science‘
Ed Seidel, NSF

VREs - VERA

VREs – My Experiment

VREs – Cancer Imaging
19/12/2014 slide 55
VRE Toolkit for
SP2010
Cancer Imaging VRE (VRE-CI) to provide a framework to allow researchers and clinicians involved in Cancer Imaging to share information, images
and algorithms. Builds on the Research Information Centre (RIC) developed for bioscience researchers by the British Library and Microsoft
Corporation.

VREs - AMI
19/12/2014 slide 56
56
• AMI - a prototype of a natural user interface system that allows bench scientists to interact with their experimental
information at the fumehood, using innovative modes of communication appropriate to the lab setting, focusing on
voice recognition, touch-screens and laser keyboards.
The Ami experiment selection screen
Log in using ID badge
(Touch-A-Tag RFID reader)
The Ami event log screen
All chemicals and apparatus tagged with
an RFID tag
http://amiproject.wordpress.com

VREs – Blog My Data
19/12/2014 slide 57
• Allows environmental scientists to visually and interactively explore large datasets, then create notes
and annotations about the data.
www.blogmydata.org
www.rdg.ac.uk/godiva2
+ =
blogs.chem.soton.ac.uk

CloudBIM – Data Collaboration and Management
 Building Information
Management
 Many different types of
roles and organisations
involved in designing,
building and managing a
building over its lifetime
 Data sharing and
collaboration facilities
limited
 Developing Cloud-based
workflow and storage for
all information around a
building, from design
down to demolition
19/12/2014 slide 58
Image courtesy of CloudBim Project http://cloudresearch.jiscinvolve.org/wp/category/projects/cloudbim/

Clouds in Space
Millions of particles in
orbit pose serious risks
for satellites and space
craft
Ever growing amount of
sensor data on these
objects
Large scale and flexible
computing infrastructure
needed to analyse the
data and calculate most
efficient flight path for
removal vehicle

Understanding the Riots – Social Media Analysis
 Two stage project
working with social
media analysis
collaboration
 Phase 1: Use cloud
computing to analyse
Tweets from 2011 riots
(with Guardian and
others)
 Phase 2: Develop
generic toolkit for
others to reuse
19/12/2014 slide 60
http://www.flickr.com/photos/torstenreimer/6177737512/ (c) Torsten Reimer

Supporting Empirical Social Scientific Research with a VRE
 Develop an environment for combining and analysing social data sets and
real time sources such as Twitter
 Use a selection of digital research tools such as sentiment and tension
analysis, social network analysis, and geospatial plotting;
 Visualize the results
 Enable more interactive sessions to be supported with social media data,
enabling a variety of “what-if” scenarios to be supported;
 Archive and share the analysis processes and results with other
researchers for interoperable reuse and reproducible experiments.
19/12/2014 slide 61
Image courtesy http://www.cs.cf.ac.uk/cosmos/

LeafWatch & Batmobile

NaCTeM
 Funded by JISC (and partners)
as a project 2004-2011
 Brief: “to contribute to the
associated national and
international research agenda, to
establish a service for the wider
academic community, and to
make connections with industry”
 Self-sustaining since 2012,
funding from industry and
(inter)national research grants
and collaborations
 Offers text mining tools, services
and advice, some of it for free
http://nactem.ac.uk/
19/12/2014 slide 63
Peter Bury CC BY NC ND 2.0
http://www.flickr.com/photos/bury_irc/5981036346/

Benefits and Value of Text Mining
 JISC-commissioned study, undertaken by Dr
Diane McDonald, Intelligent Digital Options
and Ursula Kelly, Viewforth Consulting
 Set in the context of the Intellectual Property
Office’s Consultation on proposals to change
the UK's copyright system and the
Hargreaves review
 Report publish March 2012
19/12/2014 slide 64
 Brief:
 What is the potential for text mining and text analytic technologies
and practices in UKFHE?
 What are the costs, benefits (in particular the economic value) and
risks of exploiting this potential, for whom, both now and in the
foreseeable future?
 What are the main barriers to the exploitation of this potential, and
how might they be overcome?

Value and Benefits: Main Findings
 Use of text mining in some areas (bio-medical), much less so in others
 Significant potential for cost-savings as well as new research findings
 Uptake held back by several, interlinked barriers, most importantly legal
 Evidence of market failure suggests targeted intervention such as
copyright exemption for text mining
 Awareness raising and training critical

PR Manager
Information
Manager
Data
Manager
Technologist
PR
Manager
Project
Manager

Research has a cast list
Career of the Future: Data Scientist Study Results Infographic
EMC2 : http://www.emc.com/microsites/bigdata/infographic.htm
19/12/2014 slide 67

19/12/2014 slide 68
“Scientific fraud is rife: it's time to stand up for good science”
“Science is broken” Examples:
 psychology academics making up data,
 anaesthesiologist Yoshitaka Fujii with 172 faked articles
 Nature - rise in biomedical retraction rates overtakes rise in published
papers
 This week,
“economists have been astonished to find that a famous
academic paper often used to make the case for
austerity cuts contains major errors. Another surprise is
that the mistakes, by two eminent Harvard professors,
were spotted by a student doing his homework”
http://www.bbc.co.uk/news/magazine-22223190

19/12/2014 slide 69
Public Participation
Tim Gowers - crowd-sourced mathematics
An unsolved problem posed on his blog. 32 days – 27 people – 800
substantive contributions Emerging contributions rapidly developed or
discarded Problem solved! “Its like driving a car whilst normal research is like
pushing it”
Citizen Science
 Galaxy Zoo: Hubble
 Solar Storm Watch
 Old Weather
 Whale FM
 Ancient Lives
 Fold It (creating protein molecules)
 SETI (extra terrestrial intelligence)
 Etc.

The Open Digital World is Highly Visible
 Public Engagement with Science
–Citizen Science
–Public Critique
• “Climate-gate”
• Tree rings data
–Scrutiny of public funding
 Persistence of Digital Footprint
–Social network embarrassments
–Working in the public eye
–Digital information cannot be revoked
 Need for skills for conduct and communication with the general public not
just peers
19/12/2014 slide 70

Project Manager
Information
Manager
Data
Manager
Technologist
PR
Manager
Project
Manager

Gateway for Higher Education
 The G4HE project aims to engage with the BIS-funded RCUK Gateway to
Research (GtR) initiative to improve the information exchange between HEIs
and the Research Councils. The project will develop tools and interfaces to
allow both human and machine access to data held on GtR, and elsewhere
where that is required. The tools and interfaces will be based on validated
use-cases shown to have specific and demonstrable value to HEIs, and will
be subject to robust assurance on both quality and sustainability criteria. The
use cases will be used to prioritise which data improvements should be
addressed and what value this delivers for universities.

Summary

Researchers – Research Technologists – Research Support
Challenge:
which skills do researchers need?
which skills do research support need?
which skills flow between?

© Jisc 2013
Jisc permits reuse of this presentation and its contents under the terms of the
Creative Commons Attribution-Non-Commercial-No Derivative Works 2.0 UK
England & Wales Licence.
http://creativecommons.org/licenses/by-nc-nd/2.0/uk

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