November 19, 2014
The Learning Resource Metadata Initiative, describing learning resources with schema.org, and more?
Webinar Date: Wednesday, 19 November, 2014, 10:00am-11:15am EST (UTC 15:00) World Clock: http://bit.ly/1pKiCUj)
Abstract: The Learning Resource Metadata Initiative (LRMI) is a collaborative initiative that aims to make it easier for teachers and learners to find educational materials through major search engines and specialized resource discovery services. The approach taken by LRMI is to extend the schema.org ontology so that educationally significant characteristics and relationships can be expressed. In this webinar, Phil Barker and Lorna M. Campbell of Cetis will introduce schema.org and present the background to LRMI, its aims and objectives, and who is involved in achieving them. The webinar will outline the technical aspects of the LRMI specification, describe some example implementations and demonstrate how the discoverability of learning resources may be enhanced. Phil and Lorna will present the latest developments in LRMI implementation, drawing on an analysis of its use by a range of open educational resource repositories and aggregators, and will report on the potential of LRMI to enhance education search and discovery services. Whereas the development of LRMI has been inspired by schema.org, the webinar will also include discussion of whether LRMI has applications beyond those of schema.org.
Presentation slides: PDF
Categories: Learning Resource Metadata Initiative (LRMI) | schema.org | search engines | markup languages
Webinar Type: Praxis
21 May 21, 2014
How to pick the low hanging fruits of Linked Data
Webinar Date: Wednesday, 21 May, 2014, 10:00am EDT (World Clock: 14:00 UTC http://bit.ly/1qLSeq1)
Abstract: The concept of Linked Data has gained momentum over the past few years, but the understanding and the application of its principles often remain problematic. This webinar offers a short critical introduction to Linked Data by positioning this approach within the global evolution of data modeling, allowing an understanding of the advantages but also of the limits of RDF. After this conceptual introduction, the fundamental importance of data quality in the context of Linked Data is underlined by applying data profiling techniques with the help of OpenRefine. Methods and tools for metadata reconciliation and enrichment, such as Named-Entity Recognition (NER), are illustrated with the help of the same software. This webinar will refer to case-studies with real-life data which can be re-used by participants to continue to explore OpenRefine at their own pace after the webinar. The case-studies have been developed in the context of the handbook "Linked Data for Libraries, Archives and Museums", which will be published by Facet Publishing in June 2014.
Categories: Metadata Modeling | Transactions on Metadata | Resource Description Framework (RDF)