Three datasets of images of approximately 1 square km of land area in Dublin City in 2007. Images were captured through use of the Fugro FLI-MAP family of LiDAR systems which capture LiDAR and still camera imagery simultaneously during a fly-over survey. Each dataset includes “forward” and “mapping” imagery comprising complementary data files in ECW and SDIA formats.

Data recovered from the project "Historic Ireland's Build Environment and Road Network Inventory Access" (HIBERNIA), which had been a web enablement of two earlier inventories: the Dublin Environmental Inventory (DEI) and the Dublin Docklands area master plan inventory (DDAMP) (both undertaken by the School of Architecture, Landscape and Civil Engineering, University College Dublin). The combined inventories include historical, geographical, and architectural information collected from 1993 to 1995 for 1,280 of Dublin's buildings.

The Urban Modelling Group (UMG) is based in the UCD School of Civil, Structural and Environmental Engineering at University College Dublin. Professor Debra F Laefer heads this group and it formed in 2006 to bridge the efforts of the architectural heritage community and those of practising engineers by introducing, adapting, and generating new technologies to help safeguard built urban heritage.

INSIGHT Centre for Data Analytics creates a healthier, safer, more productive world by empowering a data-driven society to enable better decisions by individuals, communities, business and governments. Insight brings together leading Irish academics from 5 of Ireland's leading research centres (DERI, CLARITY, CLIQUE, 4C, TRIL), previously established by Science Foundation Ireland (SFI) and the Irish Industrial Development Authority (IDA), in key areas of priority research including: The Semantic Web, Sensors and the Sensor Web, Social network analysis, Decision Support and Optimization, and Connected Health.

Photographic data regarding 444 builings in Dublin, Ireland, comprising primarily multi-layer images in Adobe PhotoShop (PSD) format. The majority of images consist of one or more photographic images that have been manpulated to create a single ortorectified image of a structure; a structure may be represented by more than one PSD file, such that 516 images in total are included in the dataset.

Data regarding 449 builings in Dublin, Ireland, comprising tables of building characteristics and attributes and an assessment of building status by a range of criteria.

User content curation is becoming an important source of preference data, as well as providing information regarding the items being curated. One popular approach involves the creation of lists. On Twitter, these lists might contain user accounts relevant to a particular topic, whereas on a community site such as the Internet Movie Database (IMDb), this might take the form of lists of sharing common characteristics. While list curation implicitly involves substantial combined effort on the part of users, researchers have rarely looked at mining the outputs of this kind of crowdsourcing activity. Here we study a large collection of movie lists from IMDb. We apply network analysis methods to a graph that reflects the degree to which pairs of movies are "co-listed", that is, assigned to the same lists. This allows us to uncover a more nuanced categorisation of movies that goes beyond simple metadata, such as genre or era.

Real-world social networks from a variety of domains can naturally be modeled as dynamic graphs. However, approaches to detecting communities have largely focused on identifying communities in static graphs. Therefore, researchers have begun to consider the problem of tracking the evolution of groups of users in dynamic scenarios. Here we describe a model for tracking communities which persist over time in dynamic networks, where each community is characterized by a series of significant evolutionary events. This model is used to motivate a scalable community-tracking strategy for efficiently identifying dynamic communities.

We provide here a new text corpus, mined from biomedical literature, which refers to the terms used to describe Saccharomyces cerevisiae ORFs.