The Semantics for e-science in an intelligent Big Data context
Sepublica 2014 is part of the ESWC Workshops. The ESWC 2014 takes place from May 25th, 2014 to May 29th, 2014 in Anissaras, Crete, Greece.
Semantic publishing is central to the openness that has been embraced by scholarly
communication, e-science, data journalism, e-government and across many other domains. This openness implies deep changes in making the semantics of the data available for integration, consumption and analysis. Researchers are moving from a narrative based communication into a data-based convincing argument. Such shift impacts all layers of scholarly; data needs to be archived and kept readily available and interoperable. Scholars across many disciplines are undergoing an important shift in their communication practices; reproducibility, smart data storage, intelligent use of the Web as a platform and not solely as a dissemination channel, business intelligence for e-science content and many others are currently a matter of discussion in the academic community.
The validation of scientific results requires reproducible methods, which can only be achieved if the same data, processes, and algorithms as those used in the original experiments are available in a complete and computationally amenable form. Although Biomedical journals often ask for “Materials and Methods” and datasets to be made available, reproducing experiments, sharing, reusing and leveraging scientific data is becoming increasingly difficult. Experimental data in scientific disciplines is a Big Data problem; how can we make effective use of scientific data, how should it be semantically represented, interlinked, reused, how to effectively represent experiments in scientific publications? How to bridge the gap between publications and data repositories?
As both, Europe and the US are embarking in big science, namely the Brain Activity Map (BAM) and the Human Brain Project (HBP) massive amounts of data will be generated. Just like in the Human Genome Project as data was produced, the needs for data management grew exponentially; eventually surpassing those inherent to laboratory work. Thus, data standards and ontologies will become more and more necessary. Gaining a deeper understanding of disorders such as schizophrenia, alzheimer, suicide and, amongst others, PTSD will require a much more sophisticated infrastructure than those we have so far seen. How are the semantic web and ontologies supporting reproducibility and replicability in e-research infrastructures. Scholarly data and documents are of most value when they are interconnected rather than independent; how are SW technologies supporting executable documents? Information retrieval in academic digital libraries is still a keyword based process, how can we calculate the semantic similarity across research related documents? What is the ontology landscape in e-science? how are these ontologies being used? how are they being developed? How are Minimal Information Standards being used in e-science?
Topics we would like to discuss during Sepublica 2014 include, but are not limited to, Scientific data, semantics for scientific data, e-scholarly, e-science, interoperability in scientific data, linked science, big data in science.