New Models of Scholarly Communication Across Disciplines
Based on Scholarly Workflow Models

In recent decades, research and scholarly practices have undergone dramatic changes as a result of the emergence of an increasingly interoperable global information environment and unencumbered and affordable access to large-scale computing, high-bandwidth internet connectivity and vast stores of linked open data repositories.  Internet-based communication and social media technologies have fostered on-going dialogue, interaction and collaboration among scholars within and across traditional disciplinary lines.

A sweeping dynamic of change in scholarly practices is clearly evident.  A new culture of openness has emerged in which scholars freely share ideas, data, resources and tools and communicate with peers throughout the entire scholarly lifecycle. The growing consensus of the research community is that substantive change in institutional norms is underway and that this will add value to the larger research enterprise in many ways, benefitting nearly all stakeholders.

Yet reform of scholarly communication practices and the adoption of new models for communicating the full extent and nuances of scholarly efforts, research findings and the workflows associated with creating new knowledge proceeds at a very slow pace. Although most of the debate and criticism to date has focused on access and dissemination issues, the shortcomings are broader and deeper.

Digital scholarship, or "cyberscholarship" - that based on data and computation - is radically reshaping knowledge discovery, presentation and dissemination in many subject areas.  The processes and products of digital scholarship often involve new types of data analytics, information objects and heuristic representation of findings that cannot be accurately or completely described in current scholarly communication models. In addition, the final value of the research product is diminished unless it can naturally and easily link and become part of larger and often global data research infrastructures.  The latter is critical in inspiring new efforts and to advance on-going work.  Since open data today is globally accessible in real-time, the impact of research findings is potentially immediate and far-reaching.