OpenGLAM Benchmark Survey – Measuring the Advancement of Open Data / Open Content in the Heritage Sector.
Version
Published
Date Issued
2016
Author(s)
Type
Conference Paper
Abstract
The widespread digitization of heritage content and the increasing use of social media have triggered many heritage institutions (museums, libraries, archives) to increasingly open up collections and work processes for participation from the outside, as exemplified by open data/open content, social media use, collaborative content creation, and linked data. In order to measure the degree of openness of heritage institutions, a benchmark survey was developed and administered among institutions in several countries. In the present paper we present some of the key findings and discuss the strengths and weaknesses, as well as the challenges and opportunities related to the approach chosen to measure ‘open data’, ‘open content’, and related practices within the heritage sector. In order to give an account of the particularities of our approach we compare it to the one used for the ENUMERATE survey, an international study aimed at the measurement of digitization among heritage institutions, and to the one employed for the Open Data Barometer and the Global Open Data Census, two international efforts to survey the advancement of open government data in a large number of countries. We conclude the paper by suggesting lines for further development.
ISBN
978-92-9189-210-5
Journal
Proceedings of the international symposium on the measurement of digital cultural products
Organization
Conference
International Symposium on the Measurement of Digital Cultural Products
Publisher
UNESCO Institute for Statistics
Submitter
EstermannB
Citation apa
Estermann, B. (2016). OpenGLAM Benchmark Survey – Measuring the Advancement of Open Data / Open Content in the Heritage Sector. In Proceedings of the international symposium on the measurement of digital cultural products. International Symposium on the Measurement of Digital Cultural Products. UNESCO Institute for Statistics. https://doi.org/10.24451/arbor.9495
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