Contains bibliographic (front page) information and a representative drawing (if applicable) for each trademark registration or trademark application published that week. Incluides a list of cancelled and renewed registrations.

Contains bibliographic (front page) information and a representative drawing (if applicable) for each trademark registration or trademark application published that week. Incluides a list of cancelled and renewed registrations.

The Trademark Image Search API (beta) allows searching Trademark Images using various attributes like feature, accuracy, metricspaces and candidates. This API also allows searching Trademark documents using various metadata attributes like Specimen Description, Filing Description, Filing Basis, Owner's Name, Street Address, etc.

The Trademark Status and Document Retrieval (TSDR) API allows you to make programmatic requests for trademark case status, documents, and images. Beginning on October 2, 2020, you will need an API key to download bulk data from TSDR using the TSDR API. Using API keys will help optimize usage of our TSDR system, which will help enable users like yourself to better access the information you need from TSDR. The below resources will provide you with more information on using the TSDR API.

Contains detailed information on 7.0 million trademark applications filed with or registrations issued by the USPTO between 1870 and 2020.

Contains detailed information on 786,931 assignments and other transactions recorded at the USPTO between 1952 and 2020 and involving 1,491,485 million unique trademark properties.

ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

Round 8 Test DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering. 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. This dataset consists of 360 QA AI models using a small set of model architectures.

Round 8 Holdout DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform extractive question answering on English text. 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.

Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.