Contains data for the Representative Payee application and selection process and the Representative Payee misuse process.

Update March 2025###\r

\r From 20 March 2025, the dataset update frequency has change from monthly to weekly every Thursday.\r \r

Update April 2022###\r

\r We have replaced the .xlsx file resources for all our datasets. This was required due to the API and web page search functionality no longer being supported for .xlsx files on the Data.Gov platform.\r \r ***\r

Dataset summary###\r

\r ASIC is Australia’s corporate, markets and financial services regulator. ASIC contributes to Australia’s economic reputation and wellbeing by ensuring that Australia's financial markets are fair and transparent, and supported by confident and informed investors and consumers. \r \r Credit representatives are required to maintain their details on ASIC's registers. Information contained on the Credit Representative Register is made available to the public to search via the ASIC Connect website. \r \r Selected data from the register will be uploaded each week to www.data.gov.au. The data made available will be a snapshot of the register at a point in time. Legislation prescribes the type of information ASIC is allowed to disclose to the public. \r \r The information in the downloadable dataset includes:\r \r * Register name\r * Credit representative number\r * Credit licensee number\r * Credit representative name\r * Credit representative ABN or ACN(if applicable)\r * Date commenced\r * Date ceased (if applicable)\r * Principal business locality (representative)\r * Principal business state/territory (representative)\r * Principal business postcode (representative)\r * EDRS code\r * Credit representative authorisations \r * Cross endorsements\r \r Additional information about Credit representatives can be found via ASIC's website. To view some information you may be charged a fee. \r \r More information about searching ASIC's registers. \r

Us House Congressional Representatives serving Macon-Bibb County.

Congressional districts are the 435 areas from which members are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states, which is based on decennial census population counts, each state with multiple seats is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The boundaries and numbers shown for the congressional districts are those specified in the state laws or court orders establishing the districts within each state.

Congressional districts for the 108th through 112th sessions were established by the states based on the result of the 2000 Census. Congressional districts for the 113th through 115th sessions were established by the states based on the result of the 2010 Census. Boundaries are effective until January of odd number years (for example, January 2015, January 2017, etc.), unless a state initiative or court ordered redistricting requires a change. All states established new congressional districts in 2011-2012, with the exception of the seven single member states (Alaska, Delaware, Montana, North Dakota, South Dakota, Vermont, and Wyoming).

For the states that have more than one representative, the Census Bureau requested a copy of the state laws or applicable court order(s) for each state from each secretary of state and each 2010 Redistricting Data Program state liaison requesting a copy of the state laws and/or applicable court order(s) for each state. Additionally, the states were asked to furnish their newly established congressional district boundaries and numbers by means of geographic equivalency files. States submitted equivalency files since most redistricting was based on whole census blocks. Kentucky was the only state where congressional district boundaries split some of the 2010 Census tabulation blocks. For further information on these blocks, please see the user-note at the bottom of the tables for this state.

The Census Bureau entered this information into its geographic database and produced tabulation block equivalency files that depicted the newly defined congressional district boundaries. Each state liaison was furnished with their file and requested to review, submit corrections, and certify the accuracy of the boundaries.

The dataset contains two images taken at two wavelength (blue and red) of human metaphasic chromosomes (DAPI stained) hybridized with a Cy3 labelled telomeric probe. The two images can be combined into a color image. The previous dataset of overlapping chromosomes was generated chromosomes belonging to this metaphase.

Update April 2022

We have replaced the .xlsx file resources for all our datasets. This was required due to the API and web page search functionality no longer being supported for .xlsx files on the Data.Gov platform.

Update November 2018 - frequency change to Australian Financial Services Authorised Representatives dataset

From 15 November 2018, the Australian Financial Services Authorised Representative dataset will be updated weekly every Thursday.

Dataset summary

ASIC is Australia’s corporate, markets and financial services regulator. ASIC contributes to Australia’s economic reputation and wellbeing by ensuring that Australia's financial markets are fair and transparent, and supported by confident and informed investors and consumers.

Australian Financial Services Representatives are required to maintain their details on ASIC's registers. Information contained on the Australian Financial Services Representatives Register is made available to the public to search via the ASIC Connect website.

Selected data from the register will be uploaded each month to www.data.gov.au. The data made available will be a snapshot of the register at a point in time. Legislation prescribes the type of information ASIC is allowed to disclose to the public.

The information in the downloadable dataset includes:

• Register Name
• Australian Financial Services Representative number
• Australian Financial Services Licence number
• Representative name
• ABN
• Organisation Number (eg ACN)
• Other role
• Date representative was appointed
• Appointment status
• Date representative appointment ceased (if applicable)
• Australian Financial Services Representative's principal business Address suburb
• Australian Financial Services Representative's principal business Address State/Territory
• Australian Financial Services Representative's principal business Address postcode
• Australian Financial Services Representative's principal business Address Country
• Cross endorsements
• Authority to appoint other representatives (Yes/No)
• Appointing authorised representative number (if applicable)
• Australian Financial Services authorisations
• Same authorisations as licensee (Yes/No)
• Australian Financial Services Representative related business names

Additional information about financial advisers can be found via ASIC's website. Accessing some information may attract a fee.

More information about searching ASIC's registers.

The Media Representative Firms industry consists of companies that primarily sell media time for media owners. A shift away from traditional media has led corporations to spend larger portions of their advertising budgets on digital media sources, expediting revenue growth. Industry enterprises have increasingly provided representation for online media sites, although many digital media companies opt to sell their advertising space internally and bypass the need for industry services. While online advertisements tend to be less valuable than advertisements on traditional media due to reduced commissions and revenue, demand from this market has grown exponentially. As digital advertising has grown in popularity, the pandemic led to a simultaneous sharp contraction in print advertising expenditure. Media representative firms' revenue has been increasing at an annualized 2.6% over the past five years and is expected to reach $36.9 billion in 2024, despite a dip of 0.9% in 2024 as profit reaches 13.9%. Contracts for print media representation have declined as consumers have increasingly shifted away from buying print magazines and newspapers. Direct mail and other forums for print advertising have also waned in popularity. To offset this plummet, digital advertising expenditure has significantly increased, constituting an increasing share of total advertising expenditure. Online advertising expenditure has inclined steadily and has represented an opportunity for industry entrants specializing in digital marketing placement and analytics. As corporate profit recovered following the pandemic, total advertising expenditures increased, buoying the industry. Industry revenue growth is expected to slow, declining at an annualized 0.7% over the next five years, reaching an estimated $35.6 billion in 2029 as profit slides to 13.3%. While total advertising expenditure is slated to climb, print advertising will experience a rapid sink. More internet users and a growing percentage of online businesses will continue shifting advertising budgets toward digital platforms, away from print media. An increasing focus on digital media will necessitate media representative firms to invest in new technologies and skilled employees, eating away at profit.

The Online Multi track Locating Algorithm (OML) in Hi‘Beam SEE is an algorithm that accurately extracts the position of individual ion projections in beam images. The images in this data are representative dataset images formed by preprocessing and fusing the laser and heavy ion raw data collected by Hi’beam SEE for OML algorithm training and testing.

Download In State Plane Projection Here. Boundaries for electing representatives to the Illinois House as established by that body.Update Frequency:This dataset is updated on a weekly basis.

This data set is captured from a robot workcell that is performing activities representative of several manufacturing operations. The workcell contains two, 6-degree-of-freedom robot manipulators where one robot is performing material handling operations (e.g., transport parts into and out of a specific work space) while the other robot is performing a simulated precision operation (e.g., the robot touching the center of a part with a tool tip that leaves a mark on the part). This precision operation is intended to represent a precise manufacturing operation (e.g., welding, machining). The goal of this data set is to provide robot level and process level measurements of the workcell operating in nominal parameters. There are no known equipment or process degradations in the workcell. The material handling robot will perform pick and place operations, including moving simulated parts from an input area to in-process work fixtures. Once parts are placed in/on the work fixtures, the second robot will interact with the part in a specified precise manner. In this specific instance, the second robot has a pen mounted to its tool flange and is drawing the NIST logo on a surface of the part. When the precision operation is completed, the material handling robot will then move the completed part to an output. This suite of data includes process data and performance data, including timestamps. Timestamps are recorded at predefined state changes and events on the PLC and robot controllers, respectively. Each robot controller and the PLC have their own internal clocks and, due to hardware limitations, the timestamps recorded on each device are relative to their own internal clocks. All timestamp data collected on the PLC is available for real-time calculations and is recorded. The timestamps collected on the robots are only available as recorded data for post-processing and analysis. The timestamps collected on the PLC correspond to 14 part state changes throughout the processing of a part. Timestamps are recorded when PLC-monitored triggers are activated by internal processing (PLC trigger origin) or after the PLC receives an input from a robot controller (robot trigger origin). Records generated from PLC-originated triggers include parts entering the work cell, assignment of robot tasks, and parts leaving the work cell. PLC-originating triggers are activated by either internal algorithms or sensors which are monitored directly in the PLC Inputs/Outputs (I/O). Records generated from a robot-originated trigger include when a robot begins operating on a part, when the task operation is complete, and when the robot has physically cleared the fixture area and is ready for a new task assignment. Robot-originating triggers are activated by PLC I/O. Process data collected in the workcell are the variable pieces of process information. This includes the input location (single option in the initial configuration presented in this paper), the output location (single option in the initial configuration presented in this paper), the work fixture location, the part number counted from startup, and the part type (task number for drawing robot). Additional information on the context of the workcell operations and the captured data can be found in the attached files, which includes a README.txt, along with several noted publications. Disclaimer: Certain commercial entities, equipment, or materials may be identified or referenced in this data, or its supporting materials, in order to illustrate a point or concept. Such identification or reference is not intended to imply recommendation or endorsement by NIST; nor does it imply that the entities, materials, equipment or data are necessarily the best available for the purpose. The user assumes any and all risk arising from use of this dataset.

Stores information about appointed representatives used for reporting purposes.

This dataset is about books. It has 6 rows and is filtered where the book subjects is Representative government and representation-Case studies. It features 9 columns including author, publication date, language, and book publisher.

Congressional district boundaries, enacted November 4, 2021, effective beginning with the elections in 2022 for the 118th U.S. Congress. The districts will remain in effect for the 118th-122th U.S. Congress, 2023-2032. Created by the Legislative Services Agency using Code of Iowa Chapter 41, using 2010 Census geographies and populations. For a comprehensive overview of Iowa's redistricting process, see the "Legislative Guide to Redistricting in Iowa": https://www.legis.iowa.gov/DOCS/Central/Guides/redist.pdf

And the 5% level of significance is selected.

State Representative District 60

There are 435 members of the House of Representatives in any congressional sitting. In the 118th Congress which began in January 2023, there were 58 Black members, 16 Asian American members, 54 Hispanic members.

The "Find a Veterans Representative" tool helps Veterans in Connecticut identify their local Municipal Veterans Representative. These representatives serve as the initial point of contact in each municipality for Veterans seeking assistance. The tool is based on the Municipal Veterans Representative Program established by Connecticut General Statutes §27-135.Classifications:• OPM, DVA• Authoritativeness: Non-Authoritative• Sensitivity: Public• Usage: Public UseCurrency (time):• Created: September 2024• Update Frequency (estimated): as necessary• Last Updated: May 2025Lineage:• Originated: CT Department of Veterans Affairs

Data of distribution of registered electors for Indigenous Inhabitant Representative Election, Resident Representative Election and Kaifong Representative Election by respective Rural Committees

The AC (std) and NMI (std) of clustering results on pavia centre image.

State Representative District 64

Polygon geometry with attributes displaying boundaries of the Louisiana House of Representative Districts in East Baton Rouge Parish, Louisiana.