Exploring the HI Universe with ASKAP

The survey speed of ASKAP makes it a prime instrument with which to survey the HI universe, enabling it to carry out both wide surveys of the entire sky, as well as deep surveys covering cosmologically representative volumes. Here, the use of ASKAP to study deep HI fields is discussed as proposed by the Deep Investigation of Neutral Gas Origins (DINGO) survey. This ASKAP science survey project anticipates observing in excess of 10^5 sources out to redshift z~0.4. Key science goals include: Omega_HI and its evolution, the cosmic web as traced by distributions such as the HI mass function and the 2pt correlation function, and the formation and evolution of galaxies. Science returns are maximised by targeting the GAMA survey regions, enabling the HI content of galaxies to be studied and understood in full context with all the major galactic constituents over the past 4 Gyr.Comment: Panoramic Radio Astronomy conference, Groningen, The Netherlands; 2009 June 2-

100 deg2^2 Mock Galaxy Cone for HI Surveys with the Early SKA

We distribute an easy-to-use mock catalog of galaxies with detailed neutral atomic hydrogen (HI) and auxiliary molecular and optical properties. The catalog covers a field of 10-by-10 degrees and a redshift range of z=0-1.2. It contains galaxies with 21cm peak flux densities down to 1uJy and is, within this flux limit, complete for HI masses above 10^8 solar masses. Five random realisations of the catalog in ASCII format (~4GB/file) and subtables with HI flux limits of 10u Jy (~500MB/file) and 100uJy$ (~30MB/file) can be downloaded at http://ict.icrar.org/store/staff/do/s3sax.Comment: 3 pages, 1 table, 2 figure

Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience

Interdisciplinary research, nanotechnology, nanoscience, diversity, indicators, network analysis

Knowledge-sourcing strategies for cross-disciplinarity in bionanotechnology

interdisciplinarity, collaboration, bionanotechnology, research, knowledge-sourcing, molecular motors

Using noun phrases extraction for the improvement of hybrid clustering with text- and citation-based components. The example of “Information Systems Research”

The hybrid clustering approach combining lexical and link-based similarities suffered for a long time from the different properties of the underlying networks. We propose a method based on noun phrase extraction using natural language processing to improve the measurement of the lexical component. Term shingles of different length are created form each of the extracted noun phrases. Hybrid networks are built based on weighted combination of the two types of similarities with seven different weights. We conclude that removing all single term shingles provides the best results at the level of computational feasibility, comparability with bibliographic coupling and also in a community detection application