The Annual Business Survey (ABS) collected select data on technology use and production from all sampled businesses. Results of those data are provided in the ABS Technology Characteristics of Business tables. These Technology Characteristics of Businesses estimates also provide information on sex, ethnicity, race, and veteran status of U.S. employer firms with paid employees, operating during the reference year, with receipts of $1,000 or more. The ABS Technology Characteristics of Businesses cover reference year 2018.

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF).

The National Fire Research Laboratory (NFRL) operates large scale open fire calorimeters to measure the heat and combustion products for fires in the range of 50 kW to 20,000 kW. This Fire Calorimetry Database (FCD) contains results, data files and images of fire experiments conducted at the NFRL. The specimens contained in this database include single burning items, fully furnished rooms, controlled burners, well characterized fuels and real composite fuels of unknown composition.

Round 3 Test DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

Round 3 Holdout DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF).

To produce data on barriers faced when deciding how and where to conduct financial transactions and inform policy-makers on issues related to economic inclusion.

To produce data on barriers faced when deciding how and where to conduct financial transactions and inform policy-makers on issues related to economic inclusion.

To produce data on barriers faced when deciding how and where to conduct financial transactions and inform policy-makers on issues related to economic inclusion.

To produce data on barriers faced when deciding how and where to conduct financial transactions and inform policy-makers on issues related to economic inclusion.