Another publisher accuses a librarian of libel With the proliferation of scholarly journals – particularly open-access Internet journals that charge author fees – some librarians consider themselves on the front lines of the fight to preserve quality publishing. The weapon of choice for some, including Jeffrey Beall, associate professor and scholarly initiatives librarian at the University of Colorado Denver? The blog. But some publishers have taken up their own arms – including threats of lawsuits – in defense, raising questions about academic freedom and librarians in the Internet age. Via its lawyer earlier this month, the Canadian Center for Science and Education, publisher of numerous open-access journals charging several-hundred dollar author fees, sent a letter to Beall informing him that his inclusion of the company and several of its products on a list of a possible-to-probable “predatory” journals on his blog amounted to defamation and libel. No court date has been set for that case.
When to Act on a Correlation, and When Not To - David Ritter by David Ritter | 11:00 AM March 19, 2014 “Petabytes allow us to say: ‘Correlation is enough.’” - Chris Anderson, Wired Magazine, June 23, 2008 The sentiment expressed by Chris Anderson in 2008 is a popular meme in the Big Data community. “Causality is dead,” say the priests of analytics and machine learning. But inquiring whether correlation is enough is asking the wrong question. Confidence that the correlation will reliably recur in the future. The first factor—the confidence that the correlation will recur —is in turn a function of two things: the frequency with which the correlation has historically occurred (the more often events occur together in real life, the more likely it is that they are connected) and the understanding around what is causing that statistical finding. Understanding the interplay between the confidence level and the risk/reward tradeoff enables sound decisions on what action—if any—makes sense in light of a particular statistical finding.
Scholarly Open Access Open-Access Publisher Launches with 355 New Journals January 15, 2013 Template city We recently learned of the launch of one of the largest scholarly open-access publishers. It’s called Academic and Scientific Publishing, and it launched with an amazing 355 journal titles. Read the rest of this entry » Like this: One blogger likes this. Bogus New OA Publisher Association Attempts to Compete with OASPA January 9, 2013 A bogus industry association. Many have heard of OASPA (pronounced oh-ASS-puh), the Open Access Scholarly Publishers Association. Should Journalists Cite Material from Predatory Journals? January 8, 2013 Worthy of citation? by Robert Calin-Jageman and Jeffrey Beall Society benefits from the results of scientific research in many ways. Read the rest of this entry » Two Predatory Bloopers January 3, 2013 The Biocan, second door on the left. OA Journal Pays Authors for Their Work — $2,500 December 28, 2012 A selection from the journal’s website. Read the rest of this entry » December 19, 2012
Big Data: Dead By Definition, Alive In Practice There's a gap between what big data means on paper and what it really means to a business. Big data is at a crossroads. On one hand, big data is dead, the term having been used so often that it's been stripped of tangible value. On the other hand, big data has never been so alive, as more companies than ever are trying to improve so-called big data analytics. Big data by definition The term big data -- by the most commonly-used definition -- refers to data sets that are too large and complex to manage within traditional systems. [Data analysis is a do-or-die requirement for today's businesses. This is big data as it exists on paper, the end product of a meteoric hype cycle. Big data in practice In a recent TDWI research report, 88% of organizations cited structured, relational data as their primary big data type. The same research shows that only 28% of organizations are concerned that their current systems cannot scale to meet the demands of their big data projects. More Insights
Case Study Analysis Introduction to Business Winter 2006 An Approach to Case Analysis Winter 2006 What is a Case Study? A case study is a description of an actual administrative situation involving a decision to be made or a problem to be solved. It can a real situation that actually happened just as described, or portions have been disguised for reasons of privacy. Most case studies are written in such a way that the reader takes the place of the manager whose responsibility is to make decisions to help solve the problem. The Case Method as a Learning Tool The case method of analysis is a learning tool in which students and Instructors participate in direct discussion of case studies, as opposed to the lecture method, where the Instructor speaks and students listen and take notes. Assigned cases are first prepared by students, and this preparation forms the basis for class discussion under the direction of the Instructor. How to do a Case Study Beforehand (usually a week before), you will get: Be realistic!
Big data is dead, long live big data: Thoughts heading to Strata A recent VentureBeat article argues that “Big Data” is dead. It’s been killed by marketers. That’s an understandable frustration (and a little ironic to read about it in that particular venue). As I said sarcastically the other day, “Put your Big Data in the Cloud with a Hadoop.” You don’t have to read much industry news to get the sense that “big data” is sliding into the trough of Gartner’s hype curve. That’s natural. Big data is not a term I’m particularly fond of. Whether or not Moore’s Law continues indefinitely, the real importance of the amazing increase in computing power over the last six decades isn’t that things have gotten faster; it’s the size of the problems we can solve has gotten much, much larger. In the next year, we’ll slog through the cynicism that’s a natural outcome of the hype cycle.