One of the primary modes of scholarly communication has been publishing scholarly works in form of articles, books and research papers. With the advancement in technology, steps in scholarly communication such as authoring, reviewing and reading happen using electronic information systems. However, integrated solutions have been lacking in most disciplines, and this causes inefficiency and loss of information. For example, word processor lack direct access to data that authors may want to interpret in a paper. Also, while authors have a rich and detailed understanding of the structure and characteristics of the data that a document is based on, word processors can not currently capture such structural information as they have been designed for layouting documents to be consumed by human readers only, not for enabling information systems to manage knowledge. Readers are forced to seeing a single frozen view on the underlying data in a paper; they are unable to access the full extent and the further dimensions of the data and to make their own observations beyond the restricted scope chosen by the author. Such discontinuities between steps in scholarly communication not only makes reproducibility in scholarly work harder, but also slows down information velocity1 of the sciences.
Integrated solutions should consider the questions highlighted earlier. This would enable readers to see the further dimensions of the data presented in the same environment in which the author has presented data. Similarly, reviewers and readers would be able to repeat the computations done by the author to achieve similar results. Moreover, they would be able to reuse the data and be able to extend the study. Such developments will facilitate reproducibility in scholarly communication and increase the “information velocity” of the sciences.
[FH09] Peter Fox and James A. Hendler. “Semantic eScience: encoding meaning in next-generation digitally enhanced science”. In: The Fourth Paradigm: Data Intensive Scientific Discovery. 2009, pp. 147–152.
[Han+09] Charles D. Hansen et al. “Visualization for data-intensive science”. In: The Fourth Paradigm: Data-Intensive Scientific Discovery. 2009, pp. 153–163.
[HTT09] Tony Hey, Stewart Tansley, and Kristin M. Tolle. “Jim Gray on eScience: a transformed scientific method”. In: The Fourth Paradigm: Data-Intensive Scientific Discovery. 2009.
[Pen11] Roger D Peng. “Reproducible Research in Computational Science”. In: Science 334 (2011), pp. 1226–1227.
[Aue+13] Sören Auer et al. “Introduction to Linked Data and Its Lifecycle on the Web”. In: Proceedings of the 9th International Conference on Reasoning Web: Semantic Technologies for Intelligent Data Access. RW’13. Mannheim, Germany: Springer-Verlag, 2013, pp. 1–90. isbn: 978-3-642-39783-7.
1 Reusing the terminology used by JIM GRAY in [HTT09]
2 National Research Council, http://sites.nationalacademies.org/NRC/index.htm; Computer Science and Telecommunications Board, http://sites.nationalacademies.org/cstb/index.htm.