Measure the disciplinary roots throughout your complete NASA Astrobiology Institute. Clustering bibliometric knowledge at this degree can describe the structure of a researcher, journal or an entire subject, and suggest productive future directions. It is important to use an unsupervised clustering methodology as a result of a canonical set of astrobiology documents with which to train a clustering technique doesn’t exist. We find that the vast majority of the UHNAI team is engaged in interdisciplinary research, and suggest that our method may very well be applied to additional NASA Astrobiology Institute teams specifically, or different interdisciplinary analysis teams extra broadly, to determine and facilitate collaboration opportunities. While we agree with this place, it occurs that journals are the popular technique of communication inside the great majority of the fields that compose the UHNAI workforce; due to this fact, the present examine is not hindered by this limitation. They are lifelong students who by no means move up an opportunity to increase their horizons.

Moreover, we suggest an iterative process to determine specific publications that bridge diverse fields, to facilitate interdisciplinary collaborations and ease the cognitive load of a single researcher who wishes to integrate knowledge from multiple disciplines. Furthermore, we assess the extent to which Journal Subject Classes from the Thomson Reuters Net of information database suite are enough for labelling astrobiology documents. The same is true of these references that are cited in our UHNAI papers. Particularly, we combine all of the abstracts of the entire references cited by a UHNAI publication, and use these aggregated abstracts to represent every publication. ” (Small, 2010), but Upham and Small (2010) propose a strategy to establish rising “research fronts”, extremely cited micro-specialty areas that transcend present fields. A examine by Rafols and Meyer (2010) combines backside-up and top-down approches to measure both disciplinary variety and information integration. In these studies, SCs have been employed as de facto disciplinary boundaries, and as a benchmark to measure how much a given creator, journal or research space crosses scientific fields.

In this work, we do a complete study on the efficiency of sample-tube detection algorithms on a benchmark dataset collected in a consultant out of doors setting. A major limitation of studying the citations to the UHNAI papers is that it might require the database to include those papers that cite a specific work, which varies between disciplines, fields and databases. One limitation of cluster evaluation is that “… Kostoff (1998) describes how a citation analysis can serve as a “radioactive trace” of analysis impacts. In space, astronauts need clean water, and it’s not a commodity they will just pop over to the store for when they’re hanging out on a space station. Astronomers, chemists, geologists, oceanographers and biologists work collectively to study knowledge from meteorite fragments to comets to the interstellar medium to address the query of the place else in the universe water, and thus life, is perhaps discovered. One of many goals of this research is to uncover the underlying structure within an astrobiology analysis staff that undertakes interdisciplinary tasks at the macro scale, but may differ within the extent of interdisciplinary work on the micro stage.

They’ve a bold, even ruthless, attitude toward life and could seem overly ambitious. For example, the University of Hawaii NASA Astrobiology Institute (UHNAI) research the origin of water within the solar system and beyond, in the context of understanding the origins of life. Astrobiology, the examine of the origin, evolution, distribution, and future of life in the universe, is a comparatively new subject comprised of researchers from a variety of scientific disciplines. As of 2011, the NASA Astrobiology Institute is comprised of 14 groups spanning ten universities in addition to NASA Ames, Goddard, and the Jet Propulsion Laboratory. We cluster a corpus of astrobiology abstracts labelled with their corresponding conflated SCs (Section 3.3), and assume that if a given cluster is comprised mostly of a single SC, then SCs are a sufficiently accurate classifier. Following van Leeuwen (2007), we distinguish between a prime-down bibliometric method, the place massive-scale tendencies at the best levels of publication aggregation are thought of (such as the analysis output of a country or university), and favor a bottom-up strategy, the place we analyze individual paperwork and the papers they cite. For example, van Raan and van Leeuwen (2002) and Porter et al. On this pilot study, we examine the use of an unsupervised machine learning clustering approach, the sequential Info Bottleneck (sIB) (Slonim et al., 2002) to help in measuring researcher interdisciplinarity.