Social Media, Privacy, and the Academic Classroom

We live in a world full of social media and portable technology that allows for the effortless access to, and sharing of, information. While this constant connection can be viewed as a benefit by some, there have been recent, sometimes embarrassing, instances throughout the world that show just how quickly any expectation of privacy can be destroyed. From pictures of poorly dressed shoppers at a grocery store to customers recording interactions with their servers at restaurants, the internet is full of media (all with the potential to go viral) created and posted without consent of all parties captured. This risk to privacy is not just limited to retail and restaurants, as being in any situation amongst people puts you at risk, including being in an academic classroom. Anyone providing in-class instruction, be they professor or librarian, can be at risk for this type of violation of privacy. In addition, the students in the class are also at risk for being unwittingly captured by their classmates. To combat this, colleges and universities are providing recommendations to faculty regarding this issue, such as including suggested syllabus statements about classroom recording by students. In some instances, colleges and universities have instituted formal policies with strict penalties for violators. An overview of current privacy law as it relates to an academic setting is discussed as well as recent, newsworthy instances of student recording in the classroom and the resulting controversies. Additionally, there is a discussion highlighting various recommendations and formal policies that have been issued and adopted by colleges and universities around the country. Finally, advice is offered about what librarians can do to educate students, faculty, and staff about the privacy rights of others and the potential harm that could come from posting to social media and the open web images and video of others without their consent.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.