Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

Multi-lab projects are large scale collaborations between participating data collection sites that gather empirical evidence and (usually) analyze that evidence using meta-analyses. They are a valuable form of scientific collaboration, produce outstanding data sets and are a great resource for third-party researchers. Their data may be reanalyzed…

Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…

In today's digital world, higher education institutions collect and use more data than ever. However, institutional silos create barriers for stakeholders who need data for daily operations and strategy. This article presents a vision of a unified, collaborative future for data governance and actionable steps stakeholders can take.

The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA's main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated…

Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…

This article explores potential uses, misuses, beneficiaries, and tensions of learning analytics in higher education. While those promoting and using learning analytics generally agree that ethical practice is imperative, and student privacy and rights are important, navigating the complex maze of ethical dilemmas can be challenging, particularly…

Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…

Amid the increasing reliance on digital tools and services in education, this article examines the datafication and commodification of student life in Denmark. We analyse the web and app (iOS and Android) versions of 45 tools and services that teachers in Danish public primary schools use as part of their teaching, the types of data generated by…

Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education,…

In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

In today's online data-driven world, people constantly shed data and deposit digital footprints. When individuals access health services, governments and health providers collect and store large volumes of health information about people that can later be retrieved, linked and analysed for research purposes. This can lead to new discoveries in…

Biomedical data science education faces the challenge of preparing students for conducting rigorous research with increasingly complex and large datasets. At the same time, philosophers of science face the challenge of making their expertise accessible for scientists in such a way that it can improve everyday research practice. Here, we…

In 2009, John Hattie's book Visible Learning: A Synthesis of over 800 Meta-Analyses Relating to Achievement brought big data to education. In the decade and a half since Visible Learning was originally published it has been aggressively marketed and has now grown into a large suite of branded books, tools, and products. Visible Learning continues…

As a result of the growing commercial marketplace for teachers' digital data, a new organization that includes educational data brokers has evolved. Educational data brokerage is relatively intangible due to the ease of de-identified data being collected and sold via educational technology. There is an urgent need to expose how the brokerage of…