Related papers: Promoting Open Science Through Research Data Manag…
Causal inference from observational data is the goal of many data analyses in the health and social sciences. However, academic statistics has often frowned upon data analyses with a causal objective. The introduction of the term "data…
Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source…
Objective: To (1) demonstrate the implementation of a data science platform built on open-source technology within a large, academic healthcare system and (2) describe two computational healthcare applications built on such a platform.…
Data sharing by researchers is a centerpiece of Open Science principles and scientific progress. For a sample of 6019 researchers, we analyze the extent/frequency of their data sharing. Specifically, the relationship with the following four…
Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, from…
In materials sciences, a large amount of research data is generated through a broad spectrum of different experiments. As of today, experimental research data including meta-data in materials science is often stored decentralized by the…
There has been an increasing recognition of the value of data and of data-based decision making. As a consequence, the development of data science as a field of study has intensified in recent years. However, there is no systematic and…
The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of…
In the implementation and use of research information systems (RIS) in scientific institutions, text data mining and semantic technologies are a key technology for the meaningful use of large amounts of data. It is not the collection of…
Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed by such models. While data sources are…
Technology is generating a huge and growing availability of observa tions of diverse nature. This big data is placing data learning as a central scientific discipline. It includes collection, storage, preprocessing, visualization and,…
Research in operations management has traditionally focused on models for understanding, mostly at a strategic level, how firms should operate. Spurred by the growing availability of data and recent advances in machine learning and…
Data Science is a modern Data Intelligence practice, which is the core of many businesses and helps businesses build smart strategies around to deal with businesses challenges more efficiently. Data Science practice also helps in automating…
Scientific processes rely on software as an important tool for data acquisition, analysis, and discovery. Over the years sustainable software development practices have made progress in being considered as an integral component of research.…
The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature…
This is a personal perspective on data sharing in the context of public data releases suitable for generic analysis. These open data can be a powerful tool for expanding the science of high energy physics, but care must be taken in when,…
The continuous increase in the availability of data of any kind, coupled with the development of networks of high-speed communications, the popularization of cloud computing and the growth of data centers and the emergence of…
In the recent years, there has been significant advancement in the areas of scientific data management and retrieval techniques, especially in terms of standards and protocols for archiving data. Oak Ridge National Laboratory Distributed…
Citizen science projects recruit members of the public as volunteers to process and produce datasets. These datasets must win the trust of the scientific community. The task of securing credibility involves, in part, applying standard…
As Open Access continues to gain importance in science policy, understanding the proportion of Open Access publications relative to the total research output of research-performing organizations, individual countries, or even globally has…