OpenGLAM Benchmark Survey Measuring the Advancement of Open Data / Open Content in the Heritage SectorBeat Estermann, 9 May 2016 – International Symposium on the Measurement of Digital Cultural Products, Montreal▶ Bern University of Applied Sciences | E-Government Institute

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▶ G(alleries) L(ibraries) A(rchives) M(useums)▶ OpenGLAM stands for «Open Data/Open Content» and new

participatory approaches in the cultural heritage domain

What is OpenGLAM?

1. Release digital information about the artefacts (metadata) into the public domain using an appropriate legal tool such as the Creative Commons Zero Waiver.

2. Keep digital representations of works for which copyright has expired (public domain) in the public domain by not adding new rights to them.

3. When publishing data make an explicit and robust statement of your wishes and expectations with respect to reuse and repurposing […]

4. When publishing data use open file formats which are machine-readable.

5. Opportunities to engage audiences in novel ways on the web should be pursued.

Full version with examples: http://openglam.org/principles/

The 5 OpenGLAM Principles

Early Adopters13.5%

Shar

e of

inst

itutio

ns (

%)

Innovators2.5%

Early Majority

34%

Late Majority34%

Laggards16%

OpenGLAM Benchmark Survey: Research Questions

Where do heritage institutions stand with regard to……Open Data?…Linked Data / Semantic Web?…Digitization…Open Content?…Engaging Audiences on the Internet…Collaborative Content Creation

What are the perceived risks and opportunities? (drivers vs. hindering factors)What are the expected benefits?What are the differences between different types of heritage institutions?

International comparisons: In what ways does the situation vary in different countries?

Awareness Evaluation

AdoptionTrialInterest

Innovation Diffusion Model, Everett Rogers, 1962

▶ Diffusion of Internet-related practices among heritage institutions

▶ Adoption rates for the different practices▶ Interdependencies between the adoption of various practices▶ Further factors influencing the adoption of various practices

(institution’s characteristics & country-level variables)

▶ Observed changes in attitudes

▶ Driving forces and hindering factors regarding the adoption of «open content» and «crowdsourcing» from the point of view of the institutions

▶ Country comparisons

Selection of Key Findings

Bulgaria, Brazil, Finland, New Zealand, Poland, Portugal, Switzerland, The Netherlands, Ukraine, all institution types combined, N = 1030.Cases with «stagnation» / «discontinuance» have been ignored.

Prop

ortio

n of

inst

itutio

ns (

%)

Innovators2.5%

Early Majority

34%

Late Majority34%

Early Adopters13.5%

Laggards16%

Collaborative content creation

Social media

Open content

Digitization

Linked data

Open data

Advanced implementationAdoptionTrialEvaluationInterestNo interest

Everett Roger’s Diffusion of Innovation Model

Diffusion of Innovative Practices among Heritage Institutions

Factors influencing the adoption of Internet-related practices

Country-level variablesCorrelations

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

1 -.613 ** -.107 ** .892 ** .570 ** -.285 ** .889 ** .670 ** .711 ** -.518 **

.000 .001 .000 .000 .000 .000 .000 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

-.613 ** 1 .617 ** -.356 ** -.189 ** .103 ** -.389 ** .033 -.773 ** .340 **

.000 .000 .000 .000 .001 .000 .296 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

-.107 ** .617 ** 1 .042 .197 ** .323 ** .041 .323 ** -.263 ** -.150 **

.001 .000 .179 .000 .000 .184 .000 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

.892 ** -.356 ** .042 1 .811 ** -.022 .980 ** .878 ** .612 ** -.395 **

.000 .000 .179 .000 .482 .000 .000 .000 .000

1028 1028 1028 1030 1030 1030 1028 1028 1028 924

.570 ** -.189 ** .197 ** .811 ** 1 .531 ** .860 ** .754 ** .613 ** -.063

.000 .000 .000 .000 .000 .000 .000 .000 .056

1028 1028 1028 1030 1030 1030 1028 1028 1028 924

-.285 ** .103 ** .323 ** -.022 .531 ** 1 .058 .039 .192 ** .353 **

.000 .001 .000 .482 .000 .064 .211 .000 .000

1028 1028 1028 1030 1030 1030 1028 1028 1028 924

.889 ** -.389 ** .041 .980 ** .860 ** .058 1 .837 ** .699 ** -.416 **

.000 .000 .184 .000 .000 .064 .000 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

.670 ** .033 .323 ** .878 ** .754 ** .039 .837 ** 1 .224 ** -.319 **

.000 .296 .000 .000 .000 .211 .000 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

.711 ** -.773 ** -.263 ** .612 ** .613 ** .192 ** .699 ** .224 ** 1 -.318 **

.000 .000 .000 .000 .000 .000 .000 .000 .000

1028 1028 1028 1028 1028 1028 1028 1028 1028 924

-.518 ** .340 ** -.150 ** -.395 ** -.063 .353 ** -.416 ** -.319 ** -.318 ** 1

.000 .000 .000 .000 .056 .000 .000 .000 .000

924 924 924 924 924 924 924 924 924 924

**.

mac

ro- l

evel

mes

o-

▶ Calculated as part of the UN E-Government Survey

▶ Three Sub-Indexes:

▶ E-Information Sharing: Use of online services to facilitate provision of information by governments to citizens

▶ E-Consultation: Interaction with stakeholders

▶ E-Decision Making: Engagement in decision-making processes

E-Participation Index

▶ All Internet-related practices are self-reinforcing: higher adoption levels translate into higher scores on perceived importance and desirability

▶ Small differences, but no dramatic effects in attitudes across adoption stages

▶ Attitude changes are slow; in some cases, crucial attitude changes seem to lag behind changes of practice (e.g. with regard to «open content»)

▶ Institutions are heading for a win-win situation, based on more ‘openness’ towards and participation by users:

▶ improved visibility and perceived relevance of institutions▶ improved access to external working power and expertise▶ improved interactions and relationship with users▶ networking and community building among target audiences and

heritage institutions▶ increased sense of public ownership and responsibility among users

Observed changes in attitudes

Attitudes: Conditions for Releasing Content

N = 457

Based on data from four countries: Poland, Finland, Switzerland, and The Netherlands (N = 457)

Driving and Hindering Factors of Open Content and Crowdsourcing

Driving Factors1 Hindering Factors1

Open Content Improving the visibility of the institution and its holdings

Making content more easily available for existing users and attract new users

Facilitating networking among institutions

Improving interactions with users

Doing a better job at fulfilling the institution’s core mission

Extra time effort and expenses (digitization, documentation, rights clearance)

Feeling of loss of control

Wish to prevent commercial use of content by third parties without due compensation

Technical issues and insufficient staff skills

Crowdsourcing

Intention to get access to external expertise and to have certain tasks carried out by volunteers

Quest for an improved relationship with users/visitors (trust, loyalty, public ownership and responsibility)

Extensive preparation and follow-up

Difficulties to estimate the time scope; low planning security; continuity of data maintenance is not guaranteed

1 Factors which are of relevance for more than 50% of responding institutions

Open data Linked data / semantic web Digitization Open content Social media Collaborative content creation0%

10%

20%

30%

40%

50%

60%

70%

80%

35%

6%

42%

13%

47%

17%17%

6%

55%

19%

61%

15%

51%

23%

27%

10%

71%

11%

ArchivesMuseumsLibraries

N = 1030

Adoption Rates According to Institution Type

BG BR CH FI NL NZ PL PT UA0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Open dataN = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Linked data / semantic web

N = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%20%30%40%50%60%70%80%90%

100%

Digitization

N = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Open content

N = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%20%30%40%50%60%70%80%90%

100%

Social media

N = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Collaborative content creation

N = 1030

Adoption Rates – Country Comparison

BG BR CH FI NL NZ PL PT UA0%

10%20%30%40%50%60%70%80%90%

100%

Institutions with centrally managed metadata

N = 1030

BG BR CH FI NL NZ PL PT UA0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00OpenGLAM Index: Country Comparison

N = 1030

BG BR CH FI NL NZ PL PT UA0%

10%20%30%40%50%60%70%80%90%

100%

Pure volunteer organizations (without paid staff)

N = 1030

BG BR CH FI NL NZ PL PT UA0%

10%20%30%40%50%60%70%80%90%

100%

Institutions with no more than 1 FTE paid staff and/or volunteers

N = 1030

BG BR CH FI NL NZ PL PT UA0

50

100

150

200

250

Density of heritage institutions(number of institutions per mio. inhabitants)

N = 1030

BG BR CH FI NL NZ PL PT UA0.000.100.200.300.400.500.600.700.800.901.00

E-Government Development Index and E-Participation Index (UNPACS, 2014)

E-Government Development Index EGDI E-Participation Index EPI

BG BR CH FI NL NZ PL PT UA0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

GDP per capita (in 10’000 USD)

GDP per capita (2012) GDP per capita (2002)

Comparison with the ENUMERATE Survey

OpenGLAM Survey ENUMERATE SurveyMain purpose Measure the state of

advancement of OpenGLAM-related practices in various countries

Monitor the progress on digitization of cultural heritage across Europe

Thematic coverage

Focuses on the adoption of several Internet-related practices that build upon or are complementary to the digitizaton of cultural heritage.Includes questions about driving and hindering factors as well as future practice.

Focuses on questions relating to digitization, providing much more detail in this area than the OpenGLAM Survey.

Methodological approach

Online survey (distribution lists).Calculation of response rates.Designed to allow for country comparisons.

Online survey (open call and/or distribution lists).Controlling for a target quota per country.Not designed to allow for country comparisons.

N of countries / institutions covered

9 (10) countries / 1030 institutions

29 countries / 1951 institutions

Comparison with the Open Data BarometerOpenGLAM Survey Open Data Barometer

Main purpose Measure the state of advancement of OpenGLAM-related practices in various countries

Monitor the state of «openness» of government data

Thematic coverage

Broader in scope insofar that it covers not only the publication of data, but also aspects of online participation and collaboration.Makes no assumptions about the importance of particular collections.Does not evaluate the countries’ readiness to secure positive outcomes from OpenGLAM.Covers the impacts that arise from «open content» and «crowd-sourcing» from the perspective of heritage institutions.

Focuses on the level of legal and technical «openness» of government data in a limited number of thematic areas.Makes assumptions about the importance of certain datasets for certain purposes (e.g. transparency).Covers the countries’ readiness to secure positive outcomes from an open government data initiative.Covers the impacts that arise from open data publication.

Methodological approach

Online survey among heritage institutionsCovers the perspective of data providersFocuses on individual institutions

Expert poll among country expertsCovers the perspective of data users in quite some detailFocuses on the country level

N of countries / institutions

9 (10) countries / 1030 institutions 86 countries / not applicable

▶ ENUMERATE Survey▶ Stroeker, N., and Vogels, R. (2014). Survey Report on Digitisation

in European Cultural Heritage Institutions 2014. ENUMERATE Project.

▶ Open Data Barometer▶ World Wide Web Foundation (2015) Open Data Barometer Global Report, Second

Edition.

▶ OpenGLAM Benchmark Survey▶ Estermann, Beat (2015)

Diffusion of Open Data and Crowdsourcing among Heritage Institutions. Based on data from Finland, Poland, Switzerland, and The Netherlands. Paper Presented at the EGPA 2015 Conference, held on 26-28 August 2015 in Toulouse, France.

▶ Estermann, Beat (2016) "OpenGLAM" in Practice – How Heritage Institutions Appropriate the Notion of Openness. Paper presented at the IRSPM 2016 Conference in Hong Kong. Final Draft.

▶ Estermann, Beat (2016) OpenGLAM Benchmark Survey – Measuring the Advancement of Open Data / Open Content in the Heritage Sector. Paper presented at the International Symposium on the Measurement of Digital Cultural Products, 9-11 May 2016, Montreal, Canada. Final Draft.

References

▶ Contact Details:• Beat Estermann

E-mail: beat.estermann@bfh.chPhone: +41 31 848 34 38

▶ Project Portal «OpenGLAM Benchmark Survey»:• http://survey.openglam.ch

Thank you for your attention!