*Breakthroughs for All: Delivering Equitable Access to America’s Research - The White House By: Dr. Christopher Steven Marcum, Assistant Director for Open Science and Data Policy Dr. Ryan Donohue, AAAS Science and Technology Policy Fellow and Senior Policy Advisor President Biden has said that America can be defined in one word: Possibilities. This research, which changes our lives and transforms our world, is made possible by American tax dollars. To tackle this injustice, and building on the Biden-Harris Administration’s efforts to advance policy that benefits all of America, the White House Office of Science and Technology Policy (OSTP) released new policy guidance today to ensure more equitable access to federally funded research. Previous public access policy guidance was articulated to federal agencies in the 2013 OSTP Memorandum on Increasing Access to the Results of Federally Funded Research (2013 Memorandum). Looking forward, there are two important ways in which we will build on the 2013 Memorandum and usher in the next chapter of federal public access:
Data Mining from A to Z: Better Insights, New Opportunities Acerca el Documento Hay tantos datos y una gran cantidad de decisiones que tomar. Las organizaciones de todo el mundo se están enfrentando a este dilema. Los datos están creciendo, pero ¿y su capacidad para tomar decisiones de acuerdo con esos enormes volúmenes de datos? La analítica predictiva ayuda a evaluar lo que sucederá en el futuro. Descubra como las empresas están utilizando la mineria de datos para: Detectar Fraudes.Gestionar y Manejar el riesgo.Resolver problemas de Big Data. Acerca de SAS SAS es líder en Analytics. re3data A Look Under the Hood of Scopus AI: An Interview with Maxim Khan Since its launch earlier this year, Scopus AI has been positively reviewed in several forums, including the Scholarly Kitchen back in February. To learn a bit more about the product, I had an exchange with Maxim Khan about how Scopus AI was developed and how it functions. Max is Senior Vice President of analytics products and data platform at Elsevier, and he leads the team that developed Scopus AI. First question as a bit of an introduction to those who don’t know about Scopus AI: Tell us a bit about Scopus AI and what service it provides to users above the existing Scopus service? Scopus AI is a new generative artificial intelligence product that Elsevier launched in January. Scopus AI was developed in close collaboration with the research community and helps users in several ways: Scopus AI combines Scopus’ curated content and high-quality linked data with cutting-edge gen AI technology to help researchers. Can you tell us a bit about the technology that underpins Scopus AI?
The OpenScience Project | Open source scientific software SocialSci Strengths, Weaknesses, Opportunities, and Threats: A Comprehensive SWOT Analysis of AI and Human Expertise in Peer Review With Peer Review Week fast approaching, I’m hoping the event will spur conversations that don’t just scratch the surface, but rather dig deeply into understanding the role of peer review in today’s digital age and address the core issues peer review is facing. To me, one of the main issues is that AI-generated content has been discovered in prominent journals. A key question is, should all of the blame for these transgressions fall on the peer review process? To answer this question, I would like to ask a few more in response. The peer review system is overworked! Of course, this doesn’t mean sub-par quality reviews. Ironically, AI should be seen as a tool to ease the workload of peer reviewers, NOT to add to it. The aim of AI is to ensure that there is more time for innovation by freeing our time from routine tasks. Workflows are ideally set up in as streamlined a manner as possible. Is this an editorial function or something peer reviewers should be concerned with?
Open Data Kit OpenRefine Google Scholar’s New AI Outline Tool Explained By Its Founder | Tech & Learning Google Scholar has entered the AI revolution. Google Scholar PDF reader now utilizes generative AI powered by Google’s Gemini AI tool to create interactive outlines of research papers and provide direct links to sources within the paper. This is designed to make reading the relevant parts of the research paper more efficient, says Anurag Acharya, who co-founded Google Scholar on November 18, 2004, twenty years ago last month. In honor of Google Scholar’s 20th anniversary, Acharya shares how teachers and their students can make best use of the new AI features available through the Chrome extension Google Scholar PDF reader. Google Scholar’s New AI Tool: Making Human Research More Efficient Before AI A former professor of computer science at the University of California at Santa Barbara, Acharya grew up in India. “I got access to resources, I didn't become smarter,” he says. Utilizing AI For Deeper Research Tools and ideas to transform education.
Playing with data: our ODI open data board game | News | Open Data Institute Playing with data: our ODI open data board game For the last six months, on and off, a few of us here at the Open Data Institute have been working on an open data board game. Ellen Broad and Jeni Tennision discuss its development Board games have been experiencing a resurgence in the past few years and, perhaps unsurprisingly, there are several keen board game enthusiasts here at the ODI. The idea of an open data board game was born out of discussions between us about why Monopoly was so awful, our favourite games, and the mechanics that made them work. Open Data Institute, Pre Summit Training Discovery Day, (CC-BY-SA) There are lots of different games being tested to help explain open data concepts and benefits. The ODI open data board game The ODI open data board game is about using data to build tools that improve the world you live in. We’ve put all of the instructions and game pieces on github for people to print and play themselves. Where we are now Making the game better
Evaluating LLM “Research Assistants” and their Risks for Novice Researchers – Critical AI The Deeper Dive: RAG and System Prompts In what follows, I unpack a few of the technical processes on which these systems rely. Readers who have not already read Matthew Stone, Lauren M.E. Yet another workaround that developers came to conceive for improving the performance of LLMs for informational retrieval is RAG (retrieval augmented generation), the term for a variety of processes by through which new, “external” data can be added to a pre-trained system using data from, for example, indexed sources from the web. In general, RAG systems utilize the following steps: First, new data is collected, “chunked,” and vectorized into a database that is searchable by the LLM. Readers may already recognize that the use of RAG is fundamentally decontextualizing. Whether an LLM-based tool is using uploaded documents, retrieved chunks for an external database, or some combination of the two, the system is instructed to identify key points in the text. Building Critical AI Literacies
ROMEO - Research Western ROMEO is an online management system Western uses to manage human research ethics submissions. Western, St. Joseph’s Health Care London and Lawson Health Science Centre researchers/investigators use ROMEO to submit proposed research studies to the office of Human Research Ethics. *Please note: ROMEO is not compatible with Safari; please choose an alternate browser Create a ROMEO Account Complete and Submit the ROMEO New Investigator FormYou will receive an email from the office of Human Research EthicsFollow the instructions in the email to receive your confirmation code and set your password ROMEO Login Click Here to Login ROMEO Help If you encounter any problems or need help with ROMEO, please email ethics-romeo@uwo.ca. Other Resources available: ROMEO Training The office of Human Research Ethics provides ROMEO training sessions and one-on-one training across campus.