Semantically driven social data aggregation interfaces for Research 2.0

摘要: We propose a framework to address an important issue in the context of ongoing adoption "Web 2.0" science and research, often referred as "Science or "Research 2.0". A growing number people are linked via acquaintances online social networks such Twitter1allows indirect access huge amount ideas. These ideas contained massive human information flow [35]. That users these produce relevant data is being shown many studies [1][2][28][36]. The problem however lies discovering verifying stream unstructured items. Another related locating expert that could provide answer very specific research question. using semantic technologies (RDF2, SPARQL3), common vocabularies(SIOC4, FOAF5, SWRC6) Linked Data (DBpedia7, GeoNames8, CoLinDa9) [3][4][5] extract mine about scientific events out microblogs. Hereby we identifying persons organization them based on entities time, place topic. provides API allows quick analyzed by our system. As proof-of-concept explain, implement evaluate researcher profiling use case. It involves development focuses proposition researches topics conferences they have common. This information. demonstration application: "Researcher Affinity Browser" shows how supports developers build rich internet applications for Research 2.0. application also introduces concept "affinity" exposes implicit proximity between content produced. usability usefulness itself investigated with explicit evaluation questionnaire. user feedback led conclusions successful achievements opportunities further improve this effort.