Taxpayers in the US spend $139 billion a year on scientific research, yet much of this research is inaccessible not only to the public, but also to other scientists. This is the consequence of an exploitative scientific journal system that rewards academic publishers while punishing taxpayers, scientists, and universities. Fortunately, cheap open-access alternatives are not only possible, but already beginning to take root, suggesting a way forward to a more open and equitable system for sharing research.
Publishers are eager to put out works in translation, but this can encounter problems in the research phase. There are various ways a publisher hears about an author who piques their interest: a newspaper article with a fleeting mention of a once-popular foreign author; a glance at the bookshelf of a great-aunt who immigrated from Hungary; a rave from a foreign friend or acquaintance; a tip or submission from a translator; an agent. If a publisher is interested, then the questions that follow are: Is anything available in English? Where can I read it? Has anything by Author X been translated before? Is anybody working on it now?
With the advent of the Internet, several peer-review journals have adopted the call for open access. One of biggest open access journals is the Public Library of Science, an online, nonprofit publisher and advocacy organization founded to accelerate progress in science. While the project charges a slightly higher publication fee to cover peer review management, journal production and online hosting, PLoS makes its articles free to read, distribute and reuse. In addition, the organization accepts all papers that demonstrate scientific rigor, rather than placing an artificial cap, which allow more scientific knowledge to be generated and circulated.
Many readers across multiple generations continue to read traditional books, mass-market, paperback, and hardcover. The catch is that the readers are also reading e-books too, creating a literary environment of ink and pixels coexisting in a hybrid literary culture. Electronic versions of many books are available online. Some works in the public domain may even be downloaded for free from places like iBooks and Amazon. Electronic books are also available on a large variety of devices from smartphones to e-readers and tablets to laptops. Yet, the majority of people still like the feeling of a physical book in the hands. This is good news for the publishing industry.
Too much information can be overwhelming, but when it comes to certain types of data that are used to build predictive models to guide decision making there is no such thing as too much data. To determine whether more data is really better for predictive modeling, Enric Junqué de Fortuny and David Martens, University of Antwerp, Belgium, and Foster Provost, New York University, NY, tested nine different applications in which they built models using a particular type of data called fine-grained data, such as observing an individual's behavior in a certain setting. In this article the authors state that "certain telling behaviors may not be observed in sufficient numbers without massive data."