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This Government Contract opportunity from National Science Foundation was posted on June 10, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Data Quality Scorecard Development (R Shiny Dashboard)

Closed
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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NAICS: 541611
New
SLED
Pinellas County SBE Consultants per the Consultant Competitive Negotiations Act (CCNA)
Solicitation # 26-0853-RFQ-CCNA
Pinellas County's Office of Management and Budget is establishing a pool of certified Small Business Enterprise (SBE) consultants under the Consultant Competitive Negotiations Act (CCNA). This ongoing solicitation seeks professional services in areas such as engineering, survey and mapping, architecture, landscape architecture, planning, coastal management, and construction management. The program specifically targets work assignments that do not exceed the 150,000 dollar local market threshold. To be eligible, firms must be located in Pinellas, Hillsborough, Pasco, or Manatee counties, employ no more than 50 full-time staff, and meet specific revenue caps: a three-year average of 3 million dollars for selective goods and services or 8 million dollars for construction providers. Applicants must submit a comprehensive proposal via the OpenGov portal, including an SF-330, a professional consultant certification form, SBE certification, Florida professional licenses, and a signed insurance statement. Evaluation is based on professional personnel ability and past performance, each worth 40 points, and SBE status, worth 20 points, with a minimum score of 75 required for shortlist acceptance. Selected consultants must adhere to the Pinellas County CADD Standards Manual and Kit for Survey and Civil Engineering and maintain specific insurance coverages, including 1 million dollars for professional liability and 2 million dollars for products and completed operations. While the county establishes this qualified pool, there is no guarantee of specific work assignments.
OMB - PURCHASING

POSTED

about 22 hours ago

DEADLINE

in almost 5 years

AI Contract Overview

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This contract involves maintaining and improving an R Shiny-based dashboard designed to evaluate data source quality using established federal statistical frameworks. The tool generates automated reports in both HTML and PDF formats through R Markdown, streamlining the assessment process. Issued by the National Science Foundation's Division of Acquisition and Cooperative Support, the subcontract is categorized under NAICS code 541611. The work is to be performed in Alexandria, with a proposal submission deadline set for June 18, 2026. The contract emphasizes enhancements to ensure the dashboard remains an effective resource for data quality evaluation aligned with federal standards.

General Info

Maintain and enhance R Shiny dashboard for data quality assessment; reports generated via R Markdown.

Agency

National Science Foundation → Division Of Acq And Cooperative SupportView Agency

NAICS

541611 - Administrative Management and General Management Consulting ServicesView NAICS

Place of Performance

Alexandria, VA, 22314, USA

Set-Aside

NONE

Documents

This scope was carved out of 49100426K0004.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

America’s DataHub Consortium – NSDS Services

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyNational Science Foundation → Division Of Acq And Cooperative Support
ContactsNo contacts available
OfficeN/A
Organization / Agency
National Science Foundation → Division Of Acq And Cooperative Support
View Agency Profile
Office AddressN/A
ContactsNo contact information available

Full Description

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Maintain and enhance an R Shiny-based tool assessing data source fitness using federal statistical frameworks, with automated HTML/PDF reporting via R Markdown.

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