Chirag Jay Patel

The original promise of an Open Access model of publishing was to make research outcomes available to the public who paid for the research to have taken place through publicly funded research grants. As a result, the movement toward OA publishing has taken on a life of its own as a commercial publishing strategy, driven by many factors. Yet, how are we actually doing in fulfilling one of the fundamental promises of OA—actually getting research findings into the hands of the public, policymakers, and practitioners in a usable format that actually affects change, rather than just making research findings more accessible to researchers? The two goals are quite different! This webinar will discuss motivations and models and present case studies about how to deliver on the promise to make research outcomes truly accessible and actionable. Addressing this “Last Mile” of research communication is critical to informing and empowering those who make policies and laws, who influence responsible corporate and personal behavior, and who help shape public perception. "

The increased focus on privacy and restrictions on cookie usage is having a definite effect on what can or can't be done with academic content. Publishers want to see how their content is used. Libraries want to track usage but also to respect user privacy. What we want for our own content may not be the same as we demand of other people's content. Many organizations that provide recommendations, for example, use third-party cookies. These third-party cookies are being forbidden, and publishers should be aware of the implications. For example, a vendor may currently collect data on society members and use that data to provide targeted pharma-related adverts. With all this in mind, can we implement tools for auditing our site performance without infringing privacy regulations? While site audits have been widespread for e-commerce sites for years, it is desirable to audit the recommend and discovery capability of an academic site. Can we identify the metrics of success for recommendations for our users, without infringing privacy? How can we effectively measure site engagement when the customers don't purchase anything? Topics covered will include the use (and misuse) of APIs to enhance and measure the site's effectiveness.