GIJN: What the Experts Expect for Data Journalism in 2019

Global Investigative Journalism Network: What the Experts Expect for Data Journalism in 2019. “With the global spread of data journalism, the advent of artificial intelligence and the increasing use of big data alongside a rapid rise of disinformation, GIJN asked data journalism experts around the world what they anticipate for 2019. Here are their thoughts on the major trends, ideas and technologies that will affect how we do our jobs.”

Carnegie Mellon University: Savvy Use of Data, Technology Tells the Planet’s Story

Carnegie Mellon University: Savvy Use of Data, Technology Tells the Planet’s Story. “The story of EarthTime begins on Mars. EarthTime today is a technological platform that helps people comprehend massive amounts of data about our planet and come to grips with our biggest global challenges. But 15 years ago, people just wanted to see what the Red Planet looked like.”

ScienceDaily: Tool for nonstatisticians automatically generates models that glean insights from complex datasets

ScienceDaily: Tool for nonstatisticians automatically generates models that glean insights from complex datasets . “MIT researchers are hoping to advance the democratization of data science with a new tool for nonstatisticians that automatically generates models for analyzing raw data. Democratizing data science is the notion that anyone, with little to no expertise, can do data science if provided ample data and user-friendly analytics tools. Supporting that idea, the new tool ingests datasets and generates sophisticated statistical models typically used by experts to analyze, interpret, and predict underlying patterns in data.”

NewsMaker: Using Big Databases to find Superconductors of the Future (PRESS RELEASE)

NewsMaker: Using Big Databases to find Superconductors of the Future (PRESS RELEASE). “Superconductors are materials that conduct electricity with virtually no resistance. Superconducting materials have improved the field of magnetic resonance imaging (MRI) and have led to the development of particle colliders that can be used for research related to splitting atoms. Currently available superconducting materials can only perform at extremely low temperatures. If researchers can find superconducting materials that work at ambient temperature, electricity could be conducted over large distances without energy loss. Current approaches to searching for these materials are somewhat random, and results strongly depend on researcher’s intuition, experience and luck. Materials scientist Yoshihiko Takano of Japan’s National Institute for Materials Science and colleagues have shown that sifting through an inorganic materials database using specific search parameters can provide a more systematic way to finding superconducting materials.”

EOS: Launching an Accessible Archive of Environmental Data

EOS: Launching an Accessible Archive of Environmental Data. “… emerging community repositories are enabling scientists to easily archive and publish data with essential metadata as part of the scientific workflow. These repositories increasingly serve a critical role in enhancing data sharing and use. A new data archive seeks to play this role for the U.S Department of Energy’s (DOE) environmental science community. The new archive, called Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE), preserves, expands access to, and improves usability of data from the DOE’s research in terrestrial and subsurface environments.”