Related papers: MSR Mining Challenge: The SmartSHARK Repository Mi…

There has been a surge in the number of large and flat data sets - data sets containing a large number of features and a relatively small number of observations - due to the growing ability to collect and store information in medical…

MathRepo, located at https://mathrepo.mis.mpg.de, is an online repository for mathematical research data. In mathematics, research data comes in many different flavours. For instance, in computer algebra it most often takes the form of…

Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Sequential pattern mining…

Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, that is designed for data sharing, search and analysis. A comparative study of existing repositories is performed to analyze…

We introduce FreshStack, a holistic framework for automatically building information retrieval (IR) evaluation benchmarks by incorporating challenging questions and answers. FreshStack conducts the following steps: (1) automatic corpus…

In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search…

Dynamo is a full-stack software solution for scientific data management. Dynamo's architecture is modular, extensible, and customizable, making the software suitable for managing data in a wide range of installation scales, from a few…

In pull-based development systems, code reviews and pull request comments play important roles in improving code quality. In such systems, reviewers attempt to carefully check a piece of code by different unit tests. Unfortunately,…

Dockerfiles are one of the most prevalent kinds of DevOps artifacts used in industry. Despite their prevalence, there is a lack of sophisticated semantics-aware static analysis of Dockerfiles. In this paper, we introduce a dataset of…

To perform their daily tasks, developers intensively make use of existing resources by consulting open-source software (OSS) repositories. Such platforms contain rich data sources, e.g., code snippets, documentation, and user discussions,…

The data warehouse (DW) technology was developed to integrate heterogeneous information sources for analysis purposes. Information sources are more and more autonomous and they often change their content due to perpetual transactions (data…

Many ground-breaking advancements in machine learning can be attributed to the availability of a large volume of rich data. Unfortunately, many large-scale datasets are highly sensitive, such as healthcare data, and are not widely available…

Secondary analysis or the reuse of existing survey data is a common practice among social scientists. Searching for relevant datasets in Digital Libraries is a somehow unfamiliar behaviour for this community. Dataset retrieval, especially…

The sample inefficiency of standard deep reinforcement learning methods precludes their application to many real-world problems. Methods which leverage human demonstrations require fewer samples but have been researched less. As…

Scientific software is essential to scientific innovation and in many ways it is distinct from other types of software. Abandoned (or unmaintained), buggy, and hard to use software, a perception often associated with scientific software can…

In machine learning research, it is common to evaluate algorithms via their performance on standard benchmark datasets. While a growing body of work establishes guidelines for -- and levies criticisms at -- data and benchmarking practices…

Users increasingly expect modern search systems to offer a unified interface that seamlessly retrieves information from diverse data sources and formats. However, current information retrieval (IR) evaluation benchmarks have not kept pace…

Web archives are a valuable resource for researchers of various disciplines. However, to use them as a scholarly source, researchers require a tool that provides efficient access to Web archive data for extraction and derivation of smaller…

The success of modern machine learning hinges on access to high-quality training data. In many real-world scenarios, such as acquiring data from public repositories or sharing across institutions, data is naturally organized into discrete…

Software is increasingly produced in the form of ecosystems, collections of interdependent components maintained by a distributed community. These ecosystems act as network organizations, not markets, and thus often lack actionable…