Publications by Year: 2010

2010
Fabbiano, G.; Calzetti CDEIFGMPD ; C ;. Recommendations of the VAO-Science Council. VAO-Science Council; 2010 pp. 9. Publisher's VersionAbstract
Recommendations of the VAO-Science Council following the meeting of March 26-27, 2010. Meeting web page.
1006.2168.pdf
Kurtz M  J, Accomazzi A, Henneken E, Di Milia G, Grant C  S. Using Multipartite Graphs for Recommendation and Discovery, in Astronomical Data Analysis Software and Systems XIX.Vol 434.; 2010:155-+. Publisher's Version
Rodriguez MA, Pepe A, Shinavier J. The dilated triple. In Chbeir B, Hassanien A Emergent Web Intelligence: Advanced Semantic Technologies Springer; 2010. pp. 3-16. Publisher's VersionAbstract
The basic unit of meaning on the Semantic Web is the RDF statement, or triple, which combines a distinct subject, predicate and object to make a definite assertion about the world. A set of triples constitutes a graph, to which they give a collective meaning. It is upon this simple foundation that the rich, complex knowledge structures of the Semantic Web are built. Yet the very expressiveness of RDF, by inviting comparison with real-world knowledge, highlights a fundamental shortcoming, in that RDF is limited to statements of absolute fact, independent of the context in which a statement is asserted. This is in stark contrast with the thoroughly context-sensitive nature of human thought. The model presented here provides a particularly simple means of contextualizing an RDF triple by associating it with related statements in the same graph. This approach, in combination with a notion of graph similarity, is sufficient to select only those statements from an RDF graph which are subjectively most relevant to the context of the requesting process.
Accomazzi A. Astronomy 3.0 Style {E. Isaksson, J. Lagerstrom A H, N. Bawdekar}. Library and Information Services in Astronomy VI: 21st Century Astronomy Librarianship, From New Ideas to Action [Internet]. 2010;433:273. Publisher's Version
Henneken E  A, Kurtz M  J, Accomazzi A, Grant C, Thompson D, Bohlen E, Di Milia G, Luker J, Murray S  S. Finding Your Literature Match – A Recommender System, in Future Professional Communication in Astronomy II,. Cambridge, MA; 2010. Publisher's Version
Pepe A, Mayernik MS, Borgman CL, Sompel HVD. From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web. Journal of the American Society for Information Science and Technology [Internet]. 2010;61. Publisher's VersionAbstract
In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).
Kurtz M  J. The Emerging Scholarly Brain, in Future Professional Communication in Astronomy-II (FPCA-II). Cambridge, MA; 2010. Publisher's VersionAbstract
It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.