Sentence examples for sector datasets from inspiring English sources

There are more than 40,000 unique public sector datasets on www.data.gov.uk – the largest resource of its kind in the world – from real-time transport data to information on routine hospital activity.

Britain has huge advantages in this new world: we have the largest coherent public sector datasets, which will be the backbone of the data-driven society, as well as pioneering a scientific edge in using them.

GeoDCAT-AP is a metadata profile which is a combination of the INSPIRE metadata profile for spatial data and the W3C's DCAT application profile for public sector datasets in general.

The industry sector dataset provides us with an intermediate case in which pages deal with more focused, but semantically related topics.

Our sector liquidity dataset indicates actual stock buybacks for Russell 1000 companies were $2.0 billion daily in Q1 2008 and $1.5 billion daily in Q2 2008 (complete data for Q3 2008 are not yet available).

According to our sector liquidity dataset derived from Form 10-Q and 10-K filings, actual stock buybacks for companies in the Russell 1000 were $2.4 billion daily in Q1 2007 and $2.8 billion daily in Q2 2007.

The Board will also be responsible for setting open data standards across the public sector, publishing further datasets on the basis of public demand, and – in conjunction with the Ministry of Justice – will further develop the Right to Data and advise on its implementation.

In order to improve and sustain the agriculture sector, a robust dataset is required.

We use Danish input-output (IO) tables for the period of 2000-2007 thareavailableable from Statistics Denmark at a 130-sector classification.4 These datasets distinguish between domestic and imported deliveries and their structure is given in Table 1.

Full-volume acquisition was generated during held respiration, dataset sector (frame rate ranging between 20 and 40 frames/s) dimensions and depth were set to include both the ventricle and the atrium, assuring volume sampling rates between 15 and 25/s [ 11].

The training accuracy reached 100% when all data corresponding to a particular touch were bound together in a group for a particular block (sector), and thereby a dataset composed of 1,500 input vectors with 1,500 labels was considered as a group representing each independent touch.