The Small Business Administration maintains the Dynamic Small Business Search (DSBS) database. As a small business registers in the System for Award Management, there is an opportunity to fill out the small business profile. The information provided populates DSBS. DSBS is another tool contracting officers use to identify potential small business contractors for upcoming contracting opportunities. Small businesses can also use DSBS to identify other small businesses for teaming and joint venturing.

Use this search engine to generate custom tables of orbital and/or physical parameters for all asteroids and comets (or a specified sub-set) in our small-body database. If this is your first time here, you may find it helpful to read our tutorial. Otherwise, simply follow the steps in each section: 'Search Constraints', 'Output Fields', and finally 'Format Options'. If you want details for a single object, use the Small Body Browser instead.

A database where EPA has compiled data on public drinking water systems and whether they have certain drinking water violations. This data is collected by the states and given to the EPA. This dataset is associated with the following publication: Pennino, M., J. Compton, and S. Leibowitz. Trends in Drinking Water Nitrate Violations Across the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 13450-13460, (2017).

Nowadays web portals play an essential role in searching and retrieving information in the several fields of knowledge: they are ever more technologically advanced and designed for supporting the storage of a huge amount of information in natural language originating from the queries launched by users worldwide.A good example is given by the WorldWideScience search engine:The database is available at . It is based on a similar gateway, Science.gov, which is the major path to U.S. government science information, as it pulls together Web-based resources from various agencies. The information in the database is intended to be of high quality and authority, as well as the most current available from the participating countries in the Alliance, so users will find that the results will be more refined than those from a general search of Google. It covers the fields of medicine, agriculture, the environment, and energy, as well as basic sciences. Most of the information may be obtained free of charge (the database itself may be used free of charge) and is considered ‘‘open domain.’’ As of this writing, there are about 60 countries participating in WorldWideScience.org, providing access to 50+databases and information portals. Not all content is in English. (Bronson, 2009)Given this scenario, we focused on building a corpus constituted by the query logs registered by the GreyGuide: Repository and Portal to Good Practices and Resources in Grey Literature and received by the WorldWideScience.org (The Global Science Gateway) portal: the aim is to retrieve information related to social media which as of today represent a considerable source of data more and more widely used for research ends.This project includes eight months of query logs registered between July 2017 and February 2018 for a total of 445,827 queries. The analysis mainly concentrates on the semantics of the queries received from the portal clients: it is a process of information retrieval from a rich digital catalogue whose language is dynamic, is evolving and follows – as well as reflects – the cultural changes of our modern society.

The Financial Processing Centers layer consists of the following> Defense Finance and Accounting Services (DFAS) > DFAS like services associated with non DOD Federal Agencies > State Government Payment Centers > Internal Revenue Service payment centers (the IRS calls these 'Taxpayers Assistance Centers' > Check clearing houses including Federal Reserve locations that act as check clearing houses > Credit card payment processing centers > Defense Finance and Accounting Services provide accounting and finance services for military departments and defense agencies. Non-Defense Federal Government Equivalent agencies provide accounting and finance services for non-military government agencies. Internal Revenue Service Taxpayers Assistance Centers provided payment arrangements, account inquiries, adjustments, tax forms and preparation, and accepts payments. State Government Payment Centers provide payroll services for state government employees. Credit card clearinghouses participate in the transfer of funds for a credit card. And check clearinghouses participate in the transfer of funds for a check transaction. The basis of this dataset was information gathered from official internet websites for the agencies represented in this dataset, as well as other public domain and open source research. The name, address, phone number and geospatial location for 90% of the entities were completely verified by TGS. The locations for the balance of the entities were assigned using automated methods. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g. the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute the oldest record dates from 09/25/2006 and the newest record dates from 10/02/2006.

This dataset includes buildings occupied by the headquarters of cabinet level state government executive departments, legislative offices buildings outside of the capitol building, offices and court rooms associated with the highest level of the judicial branch of the state government, and large multi-agency state office buildings. Because the research to create this data was primarily keyed off of the headquarters of cabinet level state government agencies, some state office buildings that don't house a headquarters for such an agency may have been excluded. Intentionally excluded from this dataset are government run institutions (e.g. schools, colleges, prisons, and libraries). Also excluded are state capitol buildings. State owned or leased buildings whose primary purpose is not to house state offices have also been intentionally excluded from this dataset. Examples of these include "Salt Domes", "Park Shelters", and "Highway Garages". All entities that have been verified to have no building name, have had their [NAME] attribute set to "NO NAME". If the record in the original source data had no building name and TGS was unable to verify the building name, the [NAME] attribute was set to "UNKNOWN". All phone numbers in this dataset have been verified by TGS to be the main phone for the building. If the building was verified not to have a main phone number, the [AREA] and [PHONE] fields have been left blank. All entities located on military bases have been removed from this dataset. The text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2007/12/03 and the newest record dates from 2007/12/06.

State Government Buildings in the United States This dataset is comprised of buildings or properties that are owned or leased by state level governments. It includes buildings occupied by the headquarters of cabinet level state government executive departments, legislative office buildings outside of the capitol building, offices and court rooms associated with the highest level of the judicial branch of the state government, and large multi-agency state office buildings. Because the research to create this dataset was primarily keyed off of the headquarters of cabinet level state government agencies, some state office buildings that don't house a headquarters for such an agency may have been excluded. Intentionally excluded from this dataset are government run institutions (e.g., schools, colleges, prisons, and libraries). Also excluded are state capitol buildings, as these entities are represented in other HSIP layers. State owned or leased buildings whose primary purpose is not to house state offices have also been intentionally excluded from this dataset. Examples of these include "Salt Domes", "Park Shelters", and "Highway Garages". All entities that have been verified to have no building name have had their [NAME] value set to "NO NAME". If the record in the original source data had no building name and TGS was unable to verify the building name, the [NAME] value was set to "UNKNOWN". All phone numbers in this dataset have been verified by TGS to be the main phone for the building. If the building was verified not to have a main phone number, the [TELEPHONE] field has been left blank. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 11/27/2007 and the newest record dates from 05/28/2008.

We developed this database to identify sampling units (entities related to Chemical Science education and career in Kerala) for the study 'Women’s Career Pathway in Chemical Sciences; a Multi-stage Investigation in Kerala' using two approaches:

Using search engines and visiting official databases of government departments and institutional websites.

By asking faculties, researchers and students in the Chemical Science field to supplement the list generated by the first approach.

We hope that this database will be useful for researchers in the field and students who wish to pursue their careers in Chemical Sciences.

All authors contributed equally to this work.

This research is supported by the Royal Society of Chemistry Inclusion and Diversity Fund, 2020

State and Local Public Health Departments Governmental public health departments are responsible for creating and maintaining conditions that keep people healthy. A local health department may be locally governed, part of a region or district, be an office or an administrative unit of the state health department, or a hybrid of these. Furthermore, each community has a unique "public health system" comprising individuals and public and private entities that are engaged in activities that affect the public's health. (Excerpted from the Operational Definition of a functional local health department, National Association of County and City Health Officials, November 2005) Please reference http://www.naccho.org/topics/infrastructure/accreditation/upload/OperationalDefinitionBrochure-2.pdf for more information. Facilities involved in direct patient care are intended to be excluded from this dataset; however, some of the entities represented in this dataset serve as both administrative and clinical locations. This dataset only includes the headquarters of Public Health Departments, not their satellite offices. Some health departments encompass multiple counties; therefore, not every county will be represented by an individual record. Also, some areas will appear to have over representation depending on the structure of the health departments in that particular region. Visiting nurses are represented in this dataset if they are contracted through the local government to fulfill the duties and responsibilities of the local health organization. Effort was made by TechniGraphics to verify whether or not each health department tracks statistics on communicable diseases. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields populated by TechniGraphics. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on this field, the oldest record dates from 11/25/2009 and the newest record dates from 12/28/2009

Production systems that feature temporal and spatial integration of crop and livestock enterprises, also known as integrated crop-livestock systems (ICLS), have the potential to intensify production on cultivated lands and foster resilience to the effects of climate change without proportional increases in environmental impacts. Yet, crop production outcomes following livestock grazing across environments and management scenarios remain uncertain and a potential barrier to adoption, as producers worry about the effects of livestock activity on the agronomic quality of their land. To determine likely production outcomes across ICLS and to identify the most important moderating variables governing those outcomes, we performed a meta-analysis of 66 studies comparing crop yields in ICLS to yields in unintegrated controls across 3 continents, 12 crops, and 4 livestock species. We found that annual cash crops in ICLS averaged similar yields (-7% to +2%) to crops in comparable unintegrated sys...

PubChem contains the chemical structures of small organic molecules and information on their biological activities. PubChem includes substance information, compound structures, and bioactivity data in three primary databases, PCSubstance, PCCompound, and PCBioAssay, respectively. PubChem is integrated with Entrez, NCBI's primary search engine, and also provides compound neighboring, sub/superstructure, similarity structure, bioactivity data, and other searching features. Technical documentation at http://pubchem.ncbi.nlm.nih.gov/help.html#faq

The dataset represents Emergency Medical Services (EMS) locations in the United States and its territories. EMS Stations are part of the Fire Stations / EMS Stations HSIP Freedom sub-layer, which in turn is part of the Emergency Services and Continuity of Government Sector, which is itself a part of the Critical Infrastructure Category. The EMS stations dataset consists of any location where emergency medical service (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Ambulance services are included even if they only provide transportation services, but not if they are located at, and operated by, a hospital. If an independent ambulance service or EMS provider happens to be collocated with a hospital, it will be included in this dataset. The dataset includes both private and governmental entities. A concerted effort was made to include all emergency medical service locations in the United States and its territories. This dataset is comprised completely of license free data. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 12/29/2004 and the newest record dates from 01/11/2010.This dataset represents the EMS stations of any location where emergency medical service (EMS) personnel are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total emergency medical services capability in a given area is adequate. 2. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest. 3. A resource for Emergency Management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for Federal Government events.

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes are included due to the fact that the New Mexico Mounted Police work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/14/2006 and the newest record dates from 10/23/2009

Fire Stations in the United States Any location where fire fighters are stationed or based out of, or where equipment that such personnel use in carrying out their jobs is stored for ready use. Fire Departments not having a permanent location are included, in which case their location has been depicted at the city/town hall or at the center of their service area if a city/town hall does not exist. This dataset includes those locations primarily engaged in forest or grasslands fire fighting, including fire lookout towers if the towers are in current use for fire protection purposes. This dataset includes both private and governmental entities. Fire fighting training academies are also included. TGS has made a concerted effort to include all fire stations in the United States and its territories. This dataset is comprised completely of license free data. The HSIP Freedom Fire Station dataset and the HSIP Freedom EMS dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 01/03/2005 and the newest record dates from 01/11/2010.Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total fire fighting capability in a given area is adequate. 2. A list of resources to draw upon by surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can determine those entities that are able to respond the quickest. 3. A resource for Emergency Management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for Federal Government events.

PeptideAtlas is a multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the http://tools.proteomecenter.org/wiki/index.php?title=Software:TPP" target="_blank">Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. Results may be queried and browsed at the PeptideAtlas web site. The raw data, search results, and full builds can also be downloaded for other uses.

Hospitals in New Mexico The term "hospital" ... means an institution which- (1) is primarily engaged in providing, by or under the supervision of physicians, to inpatients > (A) diagnostic services and therapeutic services for medical diagnosis, treatment, and care of injured, disabled, or sick persons, or > (B) rehabilitation services for the rehabilitation of injured, disabled, or sick persons; (...) (5) provides 24-hour nursing service rendered or supervised by a registered professional nurse, and has a licensed practical nurse or registered professional nurse on duty at all times; ... (...) (7) in the case of an institution in any State in which State or applicable local law provides for the licensing of hospitals, > (A) is licensed pursuant to such law or > (B) is approved, by the agency of such State or locality responsible for licensing hospitals, as meeting the standards established for such licensing; (Excerpt from Title XVIII of the Social Security Act [42 U.S.C. § 1395x(e)], http://www4.law.cornell.edu/uscode/html/uscode42/usc_sec_42_00001395---x000-.html) Included in this dataset are General Medical and Surgical Hospitals, Psychiatric and Substance Abuse Hospitals, and Specialty Hospitals (e.g., Children's Hospitals, Cancer Hospitals, Maternity Hospitals, Rehabilitation Hospitals, etc.). TGS has made a concerted effort to include all general medical/surgical hospitals in New Mexico. Other types of hospitals are included if they were represented in datasets sent by the state. Therefore, not all of the specialty hospitals in New Mexico are represented in this dataset. Hospitals operated by the Veterans Administration (VA) are included, even if the state they are located in does not license VA Hospitals. Nursing homes and Urgent Care facilities are excluded because they are included in a separate dataset. Locations that are administrative offices only are excluded from the dataset. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based upon this field, the oldest record dates from 06/16/2008 and the newest record dates from 06/27/2008

911 Public Safety Answering Point (PSAP) service area boundaries in New Mexico According to the National Emergency Number Association (NENA), a Public Safety Answering Point (PSAP) is a facility equipped and staffed to receive 9-1-1 calls. The service area is the geographic area within which a 911 call placed using a landline is answered at the associated PSAP. This dataset only includes primary PSAPs. Secondary PSAPs, backup PSAPs, and wireless PSAPs have been excluded from this dataset. Primary PSAPs receive calls directly, whereas secondary PSAPs receive calls that have been transferred by a primary PSAP. Backup PSAPs provide service in cases where another PSAP is inoperable. Most military bases have their own emergency telephone systems. To connect to such system from within a military base it may be necessary to dial a number other than 9 1 1. Due to the sensitive nature of military installations, TGS did not actively research these systems. If civilian authorities in surrounding areas volunteered information about these systems or if adding a military PSAP was necessary to fill a hole in civilian provided data, TGS included it in this dataset. Otherwise military installations are depicted as being covered by one or more adjoining civilian emergency telephone systems. In some cases areas are covered by more than one PSAP boundary. In these cases, any of the applicable PSAPs may take a 911 call. Where a specific call is routed may depend on how busy the applicable PSAPS are (i.e. load balancing), operational status (i.e. redundancy), or time of date / day of week. If an area does not have 911 service, TGS included that area in the dataset along with the address and phone number of their dispatch center. These are areas where someone must dial a 7 or 10 digit number to get emergency services. These records can be identified by a "Y" in the [NON911EMNO] field. This indicates that dialing 911 inside one of these areas does not connect one with emergency services. This dataset was constructed by gathering information about PSAPs from state level officials. In some cases this was geospatial information, in others it was tabular. This information was supplemented with a list of PSAPs from the Federal Communications Commission (FCC). Each PSAP was researched to verify its tabular information. In cases where the source data was not geospatial, each PSAP was researched to determine its service area in terms of existing boundaries (e.g. city and county boundaries). In some cases existing boundaries had to be modified to reflect coverage areas (e.g. "entire county north of Country Road 30"). However, there may be cases where minor deviations from existing boundaries are not reflected in this dataset, such as the case where a particular PSAPs coverage area includes an entire county, and the homes and businesses along a road which is partly in another county. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.