Comparative studies require a baseline reference and a documented process to capture new subject data. This paper combined with its principal reference [1] presents a definitive dataset in the context of snare drum performances along with a procedure for data acquisition, and a methodology for quantitative analysis. The multi-volume dataset contains video, audio, and discrete two dimensional mo...

A knowledge base stores descriptions of entities and their relationships, often in the form of a very large RDF graph, such as DBpedia or Wikidata. The entity relatedness problem refers to the question of computing the relationship paths that better capture the connectivity between a given entity pair. This paper describes a dataset created to support the evaluation of approaches that address t...

Meta-learning tries to improve the learning process by using knowledge about already completed learning tasks. Therefore, features of dataset, so-called meta-features, are used to represent datasets. These meta-features are used to create a model of the learning process. In order to make this model more predictive, sufficient training samples and, thereby, sufficient datasets are required. In t...

This paper contributes a novel psychological dataset consisting of counselors’ behaviors during Motivational Interviewing encounters. Annotations were conducted using the Motivational Interviewing Integrity Treatment (MITI). We describe relevant aspects associated with the construction of a dataset that relies on behavioral coding such as data acquisition, transcription, expert data annotations...

Music Information Research requires access to real musical content in order to test efficiency and effectiveness of its methods as well as to compare developed methodologies on common data. Existing datasets do not address the research direction of musical track popularity that has recently received considerate attention. Existing sources of musical popularity do not provide easily manageable d...

To be able to evaluate and compare the quality of different approaches in research, general and publicly available datasets are needed. While in some areas, there exists a variety of such datasets that are constantly used by researchers, in the area of activity recognition and human activity modelling, the number of publicly available datasets is rather small. In this extended abstract, we intr...

Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data togethe...

We present NewsQA, a challenging machine comprehension dataset of over 100,000 question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting in spans of text from the corresponding articles. We collect this dataset through a fourstage process designed to solicit exploratory questions that require reasoning. A thoro...

To address drift in chemical sensing, an extensive dataset was collected over a period of three years. An array of 16 metal-oxide gas sensors was exposed to six different volatile organic compounds at different concentration levels under tightly-controlled operating conditions. Moreover, the generated dataset is suitable to tackle a variety of challenges in chemical sensing such as sensor drift...

Objective: Diabetes is one of the most common metabolic diseases. Earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. Diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. Classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...