Related papers: BOPI: A Programming Interface For Reuse Of Researc…
The ability to find data is central to the FAIR principles underlying research data stewardship. As with the ability to reuse data, efforts to ensure and enhance findability have historically focused on discoverability of data by other…
This document captures the discussion and deliberation of the FAIR for Research Software (FAIR4RS) subgroup that took a fresh look at the applicability of the FAIR Guiding Principles for scientific data management and stewardship for…
Reproducibility in the computational sciences has been stymied because of the complex and rapidly changing computational environments in which modern research takes place. While many will espouse reproducibility as a value, the challenge of…
Reproducibility of research is essential for science. However, in the way modern computational biology research is done, it is easy to lose track of small, but extremely critical, details. Key details, such as the specific version of a…
Reproducibility is increasingly important to statistical research, but many details are often omitted from the published version of complex statistical analyses. A reader's comprehension is limited to what the author concludes, without…
While automated experiments and high-throughput methods are becoming more mainstream in the age of data, empowering individual researchers to capture, collate, and contextualize their data faster and more reproducibly still remains a…
Meta-analysis is routinely performed in many scientific disciplines. This analysis is attractive since discoveries are possible even when all the individual studies are underpowered. However, the meta-analytic discoveries may be entirely…
Pyserini is an easy-to-use Python toolkit that supports replicable IR research by providing effective first-stage retrieval in a multi-stage ranking architecture. Our toolkit is self-contained as a standard Python package and comes with…
Conducting research often involves managing multiple disconnected tools for survey design, data collection, response analysis, and report generation, leading to inefficiencies, increased error risks, and challenges in ensuring…
We introduce Trove, an easy-to-use open-source retrieval toolkit that simplifies research experiments without sacrificing flexibility or speed. For the first time, we introduce efficient data management features that load and process…
Open-sourcing research publications is a key enabler for the reproducibility of studies and the collective scientific progress of a research community. As all fields of science develop more advanced algorithms, we become more dependent on…
The exponential growth in computational power and accessibility has transformed the complexity and scale of bioinformatics research, necessitating standardized documentation for transparency, reproducibility, and regulatory compliance. The…
While there are high-quality software frameworks for information retrieval experimentation, they do not explicitly support cross-language information retrieval (CLIR). To fill this gap, we have created Patapsco, a Python CLIR framework.…
Independent computational reproducibility of scientific results is rapidly becoming of pivotal importance in scientific progress as computation itself plays a more and more central role in so many branches of science. Historically,…
Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research or to build a scientific database, but there is no existing…
Replicability in machine learning (ML) research is increasingly concerning due to the utilization of complex non-deterministic algorithms and the dependence on numerous hyper-parameter choices, such as model architecture and training…
Research software is an integral part of most research today and it is widely accepted that research software artifacts should be accessible and reproducible. However, the sustainable archival of research software artifacts is an ongoing…
Background: Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As…
While results visualization is a critical phase to the communication of new academic results, plots are frequently shared without the complete combination of code, input data, execution context and outputs required to independently…
Various stakeholders, such as researchers, government agencies, businesses, and research laboratories require a large volume of reliable scientific research outcomes including research articles and patent data to support their work. These…