Link to the Open Data site for the United States Census Bureau.

A list of public developer hubs maintained by the US government.

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq

This dataset was created to compile information about Board of Adjustment (BOA) cases filed with the City of Austin. The information is retrieved daily from the City's Application MANagement and Data Automation (AMANDA) database and includes information on location, proposed variances, applicants, owners, case managers etc, if available. Note that many fields are intentionally left blank or are not filled out for various reasons.More information about the BOA process is available at http://www.austintexas.gov/boa and by using the Austin Build and Connect portal https://abc.austintexas.gov/web/permit/public-search-other.

City CELCO Agreement As Amended F1 2022-2026

Established in 1982, Government Code Section 65570 mandates FMMP to biennially report on the conversion of farmland and grazing land, and to provide maps and data to local government and the public.The Farmland Mapping and Monitoring Program (FMMP) provides data to decision makers for use in planning for the present and future use of California's agricultural land resources. The data is a current inventory of agricultural resources. This data is for general planning purposes and has a minimum mapping unit of ten acres.

Financial data relating to the purchases of goods and services by the state as well as financial disbursements through various state programs as of COB June 30, 2002.

This is the guide to navigating our open data platform.

This service provides web services used to obtain order releated data. Users of this service are intended to be healthcare providers

The latest Construction Status Report outlines the ongoing delivery of social housing across the country. It shows that 9,746 social homes are currently onsite with an additional 9,559 homes in the pipeline. In quarter 3 2021, 105 new construction schemes, (1,780 homes) were added to the pipeline.

GC skew denotes the relative excess of G nucleotides over C nucleotides on the leading versus the lagging replication strand of eubacteria. While the effect is small, typically around 2.5%, it is robust and pervasive. GC skew and the analogous TA skew are a localized deviation from Chargaff’s second parity rule, which states that G and C, and T and A occur with (mostly) equal frequency even within a strand.

Most bacteria also show the analogous TA skew. Different phyla show different kinds of skew and differing relations between TA and GC skew. This article introduces an open access database (https://skewdb.org) of GC and 10 other skews for over 28,000 chromosomes and plasmids. Further details like codon bias, strand bias, strand lengths and taxonomic data are also included.

The SkewDB database can be used to generate or verify hypotheses. Since the origins of both the second parity rule, as well as GC skew itself, are not yet satisfactorily explained, such a database may enhance our understanding of microbial DNA.

Methods The SkewDB analysis relies exclusively on the tens of thousands of FASTA and GFF3 files available through the NCBI download service, which covers both GenBank and RefSeq. The database includes bacteria, archaea and their plasmids. Furthermore, to ease analysis, the NCBI Taxonomy database is sourced and merged so output data can quickly be related to (super)phyla or specific species. No other data is used, which greatly simplifies processing. Data is read directly in the compressed format provided by NCBI.

All results are emitted as standard CSV files. In the first step of the analysis, for each organism the FASTA sequence and the GFF3 annotation file are parsed. Every chromosome in the FASTA file is traversed from beginning to end, while a running total is kept for cumulative GC and TA skew. In addition, within protein coding genes, such totals are also kept separately for these skews on the first, second and third codon position. Furthermore, separate totals are kept for regions which do not code for proteins. In addition, to enable strand bias measurements, a cumulative count is maintained of nucleotides that are part of a positive or negative sense gene. The counter is increased for positive sense nucleotides, decreased for negative sense nucleotides, and left alone for non-genic regions.

A separate counter is kept for non-genic nucleotides. Finally, G and C nucleotides are counted, regardless of if they are part of a gene or not. These running totals are emitted at 4096 nucleotide intervals, a resolution suitable for determining skews and shifts. In addition, one line summaries are stored for each chromosome. These line includes the RefSeq identifier of the chromosome, the full name mentioned in the FASTA file, plus counts of A, C, G and T nucleotides. Finally five levels of taxonomic data are stored.

Chromosomes and plasmids of fewer than 100 thousand nucleotides are ignored, as these are too noisy to model faithfully. Plasmids are clearly marked in the database, enabling researchers to focus on chromosomes if so desired. Fitting Once the genomes have been summarised at 4096-nucleotide resolution, the skews are fitted to a simple model. The fits are based on four parameters. Alpha1 and alpha2 denote the relative excess of G over C on the leading and lagging strands. If alpha1 is 0.046, this means that for every 1000 nucleotides on the leading strand, the cumulative count of G excess increases by 46. The third parameter is div and it describes how the chromosome is divided over leading and lagging strands. If this number is 0.557, the leading replication strand is modeled to make up 55.7% of the chromosome. The final parameter is shift (the dotted vertical line), and denotes the offset of the origin of replication compared to the DNA FASTA file. This parameter has no biological meaning of itself, and is an artifact of the DNA assembly process.

The goodness-of-fit number consists of the root mean squared error of the fit, divided by the absolute mean skew. This latter correction is made to not penalize good fits for bacteria showing significant skew. GC skew tends to be defined very strongly, and it is therefore used to pick the div and shift parameters of the DNA sequence, which are then kept as a fixed constraint for all the other skews, which might not be present as clearly. The fitting process itself is a downhill simplex method optimization over the three dimensions, seeded with the average observed skew over the whole genome, and assuming there is no shift, and that the leading and lagging strands are evenly distributed. The simplex optimization is tuned so that it takes sufficiently large steps so it can reach the optimum even if some initial assumptions are off.

co2 mole per mole of dry air, representative of site, Point Arena, California, United States (PTA)

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientist...

This dataset tracks annual black student percentage from 1999 to 2023 for Gov's Village Stem (Lower) vs. North Carolina and Charlotte-Mecklenburg Schools School District

The latest data for the measures of children’s well-being, complementing the UK Measures of National Well-being.

co2 mole per mole of dry air, all valid data from 92 magl intake, Zotino, Siberia, Russia (ZOT)

co2 mole per mole of dry air, representative with outliers removed, South Pole, Antarctica, United States (SPO)

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq

This dataset is a monthly upload of the Community Registry (www.AustinTexas.gov/CR), where community organizations such as neighborhood associations may register with the City of Austin to receive notices of land development permit applications within 500 feet of the organization's specified boundaries. This dataset can be used to contact multiple registered organizations at once by filtering/sorting, for example, by Association Type or by Association ZipCode. The organizations' boundaries can be viewed in the City's interactive map at www.AustinTexas.gov/GIS/PropertyProfile/ - the Community Registry layer is under the Boundaries/Grids folder.