The multitude of software tools is available for the creation of learning resources. However the majority of these tools provided by different software producers do not have a unified mechanism by means of which it would be possible to search and reuse the existing learning resources or their elements. To solve this problem the structures of descriptive data can be used. The aim of this paper is to describe a meta-model of e-learning objects and e-learning formats that could be used in the creation of e-learning materials compatible with various e-learning standards. The meta-data models that are used in widely-known learning resources' repositories and their structure's metadata standards providing cross-system compatibility have been evaluated. The key metadata standards of learning objects were identified and their comparative analysis was performed. The e-learning material logical model was created and the essential demands for elearning object's data repository were defined. The technologies and their provided electronic learning objects' classification systems were investigated for the future development of e-learning materials. The scheme of eLM development process was obtained, which provides the transformation of different modules.
This paper describes the architecture and implementation of a semantic text annotation tool for cultural heritage content. The requirements for this tool are based on text annotation case studies at the National Library of Latvia and were generalized to be applicable to a wider range of annotation projects. The tool implements a rich and flexible annotation model with support for three core types of annotations (simple, composite and structural), user-definable annotation and entity classes, and advanced functionality such as links between annotations. Information about named entities referenced from annotations is collected in an integrated entity database, accessible using a Linked Data interface.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.