SOL Experiment Data

SOL-Experiment-Data Overview
The SOL-Experiment-Data dataset presents the data acquired from the execution of the SOL-Experiments project. The SOL-Experiments case studies include queries from music (Band and Musical Artists) and movies (Film) domain. The experiments uses SOL-Engine framework to query DBpedia, retrieving not only the query results but also related data found by serendipity.
The experiment consisted of the following steps:(1-a) Retrieving a list of 10,000 entities of selected types (Band, Musical Artists and Film) from DBpedia SPARQL endpoint.(1-b) Submitting each entity to SOL-Engine in order to locate related content based on SOL-Engine serendipity patterns set (Music Influenced Analogy, Generic Hierarchy Analogy, SeeAlso Surprizing Observation, Music Association Surprizing Observation, SameAs Surprizing Observation, Different From Inversion). Each serendipity pattern is considered alone. One last configuration is used to combine all the serendipity patterns together.(2) The related content is compared to its source entity according to a dissimilarity metric that observes the retrieved labels. This analysis is used to value unexpectedness.(3) The unexpectedness score of each serendipity pattern is computed as the average of unexpectedness of each entity processed.
The data is compressed in .zip format and can be uncompressed by standard compression utilities. The dataset contains raw data (.json).
The underlying data and code can be accessed through standard text edit software.
Maintainability Plan
The SOL-Experiment-Data dataset is result of the following projects: SOL-Engine framework and SOL-Experiments. This way, as the cited projects evolve, the SOL-Experiment-Data dataset is going to be update in order to reflect the projects modification.
Additionally, there are plans to expand the dataset to include other queries, and therefore, to retrieve different entities set. This dataset update is planned to be conducted every semester. This will enable the dataset to incrementally grow with diverse scenarios.