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Empirical analyses and results by Franz Barjak, FHNW

eResearch2020 Final Workshop, 24 February 2010

eResearch 2020eResearch 2020The role of e-Infrastructures in the creation of The role of e-Infrastructures in the creation of

global virtual research communitiesglobal virtual research communities

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Content

1. Empirical tasks and approach2. e-Infrastructure case studies3. Research Communities Survey

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Analytical and empirical approach

• e-Infrastructure case studies– (Telephone) interviews– Document analysis– Extended case descriptions– Multi-case comparison

• Research Communities Survey– Exploratory online survey among users and developers of

e-Infrastructures– Descriptive statistics on responses

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E-Infrastructure case studies

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The 18 analysed cases

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Collected case data

1. Characteristics of field (Which fields? Maturity? Structures?) 2. Project Overview (Motivation? Main goals? Project

maturity? Funding?) 3. Organizational Structure (Size and composition?

Governance and division of labor?)4. Managing internal and external relations (Sustaining

involvement? Users, user recruitment? Drivers and barriers to adoption? Challenges in interdisciplinary and inter-organizational collaboration?)

5. Technology (Main technologies, resources and services? Data sharing? Interoperability?)

6. Contribution (Main contributions and challenges?)7. Informants’ recommendations to policy makers

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Sizes and domainsParticipating org. Industry Domain

EGEE > 20 (70+) Yes e-InfrastructureOSG > 20 (53) No e-InfrastructureCineGrid > 20 (50) Yes e-InfrastructureGEANT > 20 (34) No e-InfrastructureOGF > 20 Yes e-InfrastructureTeraGrid 11-20 No e-InfrastructureDEISA 11-20 No e-InfrastructureEELA-2 11-20 No e-InfrastructureDRIVER 11-20 No e-InfrastructureD4Science 11-20 No EnvironmentalC3-Grid 11-20 Yes EnvironmentalNVO 11-20 No Physical sciences & engineeringETSF 11-20 No Materials & analytical facilitiesMediGrid 5-10 No Biological & medicalSwiss Biogrid 5-10 Yes Biological & medicalCLARIN > 20 (156) No Social sciences & humanitiesDARIAH 11-20 No Social sciences & humanitiesSND 1-4 No Social sciences & humanities

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Mega projects

Funding arrangements

Regular projects

Large projects

Small projects

Funding per year

GEANT 40m €TeraGrid 31.25m US-$EGEE-III 23.575m € (48.575 m €)DEISA 6.24m €OSG 6m US-$EELA-2 2.55m €D4Science 1.96m €NVO 1.75m US-$C3-Grid 1.7m € DRIVER 1.53m €CLARIN 1.37m €ETSF 1.27m € (3.33m €)MediGrid 1.25m €CineGrid N/ASND N/AOGF N/A (< 1m US-$/year est.)Swiss Biogrid N/ADARIAH N/A

Problem: PM and even partici-pants do not have full knowledge of the bud-gets and lack data on unfunded contributions

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Governance structures

• No relationship between governance structure and project success• Scale from the small and informally organized (e.g. CineGrid) to larger

multi-tiered and more elaborate complex structure (e.g. Géant, EGEE)• Steering committees/management groups: researchers vs. externals• Permanently constituted with core staff vs. only “episodic governance” • More vs. less centralization; only in a few cases a move away from a

centralized towards a more federated or ‘flat’ organization (OGF, TeraGrid, OSG)

• Larger projects have advisory and/or steering committees of some sort– Different purposes: provide guidance, ensure ‘democratic’ representation

from among all project members or stakeholder groups

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Technologies, resources, services

User interfaces (portals, workbenches, analysis tools)

Metadata(specifications and standards for distributed

repositories)

Computing and basic technology (distributed computing, supercomputing,

visualization, security/authentication)

Networking Generic, established

- Mature and in common use- Interoperability still problematic- Grid vs. cloud computing

- Partly mature and well established- Domain differences

- Few working pilot cases- Customisation and commodification- Field differences

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User communities

• International projects usually also cross continental boundaries

• Use is difficult to assess:– Users connect through gateways or portals; – Registration and authentication are handled at a higher level

(organization);– Little monitoring of used tools and applications;– Interrupters and drop-outs are not distinguishable

• Size of communities:– Large and multidisciplinary user communities of TeraGrid, OSG, EGEE,

and DEISA; – Most others still deal with a rather narrow set of 50 to up to 200

users, mostly pilot users

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Extending use

• Not for all a top priority:– Sequential approach to technology development and diffusion– Purpose is not to serve users but advance the state-of-the-art– Prospects of continuation are already low

• Most common measures for recruiting users:– Tutorials and training– Targeted communication to potentially interested organizations and

individuals– Presentations at conferences, workshops, events– Word of mouth and social networking

• Innovative approach: Cultivating relationships to users and developing solutions which particularly address users’ needs (OSG, TeraGrid)

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Janus head of collaboration and competition

CollaborationGoal: pooling resources to move

forward on “big science” challenges

Political: institutionalizing global collaboration and world-wide

harmonisation of e-Infrastructures

Technological: advancing interoperability

Scientific/cognitive: knowledge and competences

CompetitionGoal: improving competitive

position, securing future resources

Political: rationale for e-Infrastructure investment (e.g. Lisbon strategy, NSF activities)

Technological: pushing technologies (e.g. middlewares)Scientific: funding, credits,

recognition & reputation

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Interorganizational collaboration

• Dense network of participating organizations, interorganizat-ional collaboration is a reality in e-Infrastructures

• Collaboration barriers stem from cultural and technical differences:– Field differences– Organizational identities– Different technological systems and technological pecularities

• Strategies of dealing with collaboration barriers:– Low level of embedding– Building on established interorganizational relationships– High investments of time and resources for coordination and

communication

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e-Infrastructure

Research community A

Research community B

Research community C

Developer community I

Developer community II

Professional user community a

Intricate interdisciplinary web

• Groups: with distinct interests and types of involvement

• Strongest challenges:– Negative attitude towards

technology and computer-enhanced research,

– Little understanding of domain-specific practices,

– General problems of field jargon and communication,

– Divergent objectives (cutting-edge research versus service provision)Research community A

Researcher A

Researcher B

Researcher C

Developer I

Developer II

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Bridging disciplinary boundaries

• Common measures– Web-based support (Wikis, FAQ pages, mailing lists),– Tutorials and training,– User-friendly portals,– Working with “lead users”

• Innovative approaches– Mediators or translators of user demands– Generating field-specific environments – “Brokerage”: to “broker” the development of tools and interfaces to a

partner more familiar with the requirements of a certain field.

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Research Communities Survey

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Approach

• Online survey• Distribution to contact persons in most of the

included e-Infrastructure cases• + Additional mailing to a wider set of respondents via

the BELIEF network• Exploratory: no control of the survey population,

results are not representative for any field or country• 407 usable responses in total returned

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Collected data

• Personal and professional background of the respondents (e.g. affiliation, time allocation, country of work, highest degree, field),

• Selection of one specific e-infrastructure: genesis of involvement, catalysts & barriers, sponsors, type of involvement,

• Questions on the others involved in a similar way in the selected e-infrastructure (=community), e.g. number, geographical & organizational spread,

• Use of the services and resources from the e-infrastructure, • Impact on research and collaboration networks,• Importance of national and international Grid initiatives,• Recommendations to e-infrastructure policy makers.

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Response statistics

• Geographical spread:– Europe: 61%– North-America: 10%– Latin America: 21%– Others: 8%

• Affiliation:– Academic institutions: 81%– Governments and inter-

national organizations: 13% – Private and commercial

sector: 6%• Type of involvement in e-

Infrastructure:– Research users: 46%– Other users: 9%– Developers: 45%

Field In %

Research users

Astronomy or Astrophysics 6.2

Biological Sciences and Medicine 8.2

Chemical and Material Sciences 4.6

Computer and Information Sciences 9.3

Engineering and Technology 5.2

Earth and Other Natural Sciences 4.6

Physical Sciences 5.4

Social Sciences and Humanities 3.4D

evelopersAcademic and IT support services 9.5

Supercomputing & distributed comp. 17.0

Networking 4.1

Application Development 9.0

Other 13.4

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Virtual Research Communities

21-10028%

6-2018%

1-515%

DK20%

> 5009%

100-5008%

None 2%

Globally37%

Single region

11%

Continent31%

Single country

21%

Size (est. number of colleagues) Geographical extension

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Virtual Research Communities by e-infrastructure

Size (est. number of colleagues) Geographical extension

(Differences from all responses in %)

-20.0% -10.0% 0.0% 10.0% 20.0%

None

1-5

6-20

21-100

101-500

> 500

DK

DEISAEELA2EGEENVOOther

-50.0%

-30.0%

-10.0%

10.0% 30.0% 50.0%

Single region

Singlecountry

Continent

Globally

DEISA

EELA2

EGEE

NVO

Other

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Involvement in one e-infrastructureServices & resources Catalysts & barriers

53%

37%

31%

30%

29%

28%

27%

23%

22%

20%

20%

17%

16%

11%

0% 10% 20% 30% 40% 50% 60%

Grid computing

Data management tools

Data collections

Data analysis tools

My own app. on the infra.

Online storage

Collaboration tools

Simulation

Supercomputing

Individual support/advice

Online dig. mat. for research

Visualization

Remote access to res. inst.

Other

25%

23%

6%

6%

14%

5%

5%

18%

20%

17%

8%

11%

10%

28%

0% 10% 20% 30%

Access toresources

Organizational

Technicalcapabilities

Ease of use

Funding-related

Training-related

Othercatalysts/barriers

Catalyst

Barrier

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Involvement at/after project startby activity of involvement by origin of funding

39%

39%

38%

47%

40%

37%

46%

22%

18%

32%

8%

21%

15%

38%

26%

26%

3%

3%

2%

0% 20% 40% 60% 80% 100%

from the start

1-2y after start

3-5y after start

>5y after start

all

National International Private Own org.

31%

39%

55%

68%

46%

11%

11%

8%

58%

50%

38%

22%

44%

10%

10%

0% 20% 40% 60% 80% 100%

from the start

1-2y after start

3-5y after start

>5y after start

all

Research user Other user Developer

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Importance of an e-Infrastructure for research or work

• The lack of [selected e-Infrastructure] or similar resources would impair my Research Programme ... – … not at all or little 31%– … very much 54%– … totally 15%

• The availability of [selected e-Infrastructure] or similar resources for my research work is …– … very unimportant 2%– … unimportant 3%– … neither important nor unimportant 8%– … important 31%– … very important 56%

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Importance by type of e-Infrastructure

4%

7%

7%

6%

6%

28%

5%

14%

6%

23%

15%

24%

38%

43%

32%

33%

42%

32%

40%

41%

52%

32%

55%

56%

26%

59%

36%

8%

5%

0% 20% 40% 60% 80% 100%

National

International

Disciplinary

Multidisciplinary

Computing

Data

Developers

Community

Very unimportant Unimportant Neutral Important Very important

Geographic scope

Disciplinary scope

Type of service

Driver

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Thank you!

eResearch 2020eResearch 2020The role of e-Infrastructures in the creation of The role of e-Infrastructures in the creation of

global virtual research communitiesglobal virtual research communities