Matches in Ruben’s data for { ?s ?p ?o }
- publication type Work.
- publication type Document.
- publication P50 me.
- publication P50 me.
- publication P50 me.
- publication P50 me.
- publication maker me.
- publication maker me.
- publication maker me.
- publication maker me.
- publication title "Linked Data Generation for Adaptive Learning Analytics Systems".
- publication isPartOf proceedings_of_the_linked_learning_workshop.
- publication name "Linked Data Generation for Adaptive Learning Analytics Systems".
- publication label "Linked Data Generation for Adaptive Learning Analytics Systems".
- publication name "Linked Data Generation for Adaptive Learning Analytics Systems".
- publication topic interoperability.
- publication topic Provenance.
- publication topic SPARQL.
- publication topic Linked_Data.
- publication topic RDF.
- publication subject interoperability.
- publication subject Provenance.
- publication subject SPARQL.
- publication subject Linked_Data.
- publication subject RDF.
- publication authorList b0_b2251.
- publication topic interoperability.
- publication topic Provenance.
- publication topic SPARQL.
- publication topic Linked_Data.
- publication topic RDF.
- publication abstract "According to the Learning Analytics (LA) reference model, LA is used to collect, explore and analyze diverse types and interrelationships of data. Specifications like the Experience API (xAPI) work towards interoperability with respect to interrelationship of diverse learning data. Algorithms for adaptive learning could be improved by incorporation of user-related data, not present in learning activities. Linking these user-related data with learning activity data would fully exploit the potential of interrelationships with data. Conventional solutions, as well as current Linked Data-based solutions focus purely on learning activity data, whereas solutions based on Linked Data could be used to integrate data of different domains. We propose a provenance-aware pipeline to transform xAPI learning activity statements to Linked Data. The integration of learning activities with other user data, provides a more complete set of user data, improving an adaptive learning analytics system. We use the proposed pipeline to build a Linked Learning Record Store based on the Resource Description Framework (RDF). SPARQL queries are used to link data about learning activities, enriched with fine-grained exercise descriptions, with data describing the abilities of users. In this paper, we show how Linked Data can be generated from xAPI statements in a streaming approach, based on existing tools and interfaces. Our solution demonstrates the usage of Linked Data to combine learning activity data with user ability data, to get a more complete set of user data aiming to assist in adaptive learning.".
- publication datePublished "2018".
- publication mainEntityOfPage lieber_lile_2018.
- publication sameAs publication.
- publication isPrimaryTopicOf lieber_lile_2018.
- publication page lieber_lile_2018.
- publication author steffen_stadtmuller.
- publication author pedro_szekely.
- publication author maria_maleshkova.
- publication author me.
- publication creator steffen_stadtmuller.
- publication creator pedro_szekely.
- publication creator maria_maleshkova.
- publication creator me.
- publication about Web_data.
- publication about Web_API.
- publication about Linked_Data.
- publication about Semantic_Web.
- publication about World_Wide_Web.
- publication author steffen_stadtmuller.
- publication author pedro_szekely.
- publication author maria_maleshkova.
- publication author me.
- publication coparticipatesWith steffen_stadtmuller.
- publication coparticipatesWith pedro_szekely.
- publication coparticipatesWith maria_maleshkova.
- publication coparticipatesWith me.
- publication type PublicationVolume.
- publication type ScholarlyArticle.
- publication type Article.
- publication type Document.
- publication type Q386724.
- publication type CreativeWork.
- publication type Document.
- publication type Work.
- publication type Document.
- publication P50 steffen_stadtmuller.
- publication P50 pedro_szekely.
- publication P50 maria_maleshkova.
- publication P50 me.
- publication maker steffen_stadtmuller.
- publication maker pedro_szekely.
- publication maker maria_maleshkova.
- publication maker me.
- publication title "Proceedings of the Second Workshop on Services and Applications over Linked APIs and Data".
- publication name "Proceedings of the Second Workshop on Services and Applications over Linked APIs and Data".
- publication label "Proceedings of the Second Workshop on Services and Applications over Linked APIs and Data".
- publication name "Proceedings of the Second Workshop on Services and Applications over Linked APIs and Data".
- publication topic Web_data.
- publication topic Web_API.
- publication topic Linked_Data.
- publication topic Semantic_Web.
- publication topic World_Wide_Web.
- publication subject Web_data.
- publication subject Web_API.
- publication subject Linked_Data.
- publication subject Semantic_Web.
- publication subject World_Wide_Web.
- publication authorList b0_b3213.
- publication topic Web_data.
- publication topic Web_API.
- publication topic Linked_Data.
- publication topic Semantic_Web.
- publication topic World_Wide_Web.
- publication abstract "Current developments on the Web have been marked by the increased popularity of Linked Data and Web APIs. However, these two technologies remain mostly disjunct in terms of developing solutions and applications in an integrated way. Therefore, we aim to explore the possibilities of facilitating a better integration of Web APIs and Linked Data, thus enabling the harvesting and provisioning of data through applications and services on the Web. In particular, we focus on investigating how resources exposed via Web APIs can be used together with Semantic Web data, as means for enabling a shared use and providing a basis for developing rich applications on top.".
- publication datePublished "2014".
- publication mainEntityOfPage maleshkova_salad_2014.
- publication sameAs publication.
- publication isPrimaryTopicOf maleshkova_salad_2014.