BREC Park Amenities

This dataset displays all facilities, properties and amenities operated by the East Baton Rouge Parish Recreation and Park Commission (BREC). This includes all public parks, golf courses, community centers, and special purpose recreational facilities (such as the Baton Rouge Zoo). The amenity columns (BMX, Fishing Access, Tennis Courts, etc) indicate with a Yes or No whether that amenity exists at each park.

Land Use_data

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe’s Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe’s Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS.

Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information: Section 2

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the second spreadsheet of three in the Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information.

Crustaceans and Demersal, Large Pelagic and Small Pelagic Fish (Operational Data)

Operational data provides operational information of sampled fishing vessels that contains specifications of vessel, engine and fishing gears, and operational inputs. The variables of these data are: organization/project; ID trip; surveyor; landing site/collector; fishing ground (fisheries management area/WPP); sampling time; time; commodity; vessel name/owner; mark; vessel owner; captain name; departure; arrival; origin port; crew (individual); vessel length; vessel weight; main engine; second engine; vessel material; light power; vessel space (unit); box total (unit); space/box capacity; auxiliary vessel; auxiliary vessel; size; freezer; freezer capacity; GPS use ; GPS type; andon (mobile fishing from other provinces) vessel; andon vessel provenance; fishing gear; fishing gear specifications; value; unit; material; tools operated (unit); fishing areas; setting total; ice block total; water depth (start); water depth (real); number of days per trip; number of days per catch; FAD use; FAD visited; FAD succeeded; fishing time; soaking (hour); comment; resources; total catch for consume in volume (Kg); total catch for consume in units (Ind); total catch in volume (Kg); total catch in units (Ind); local name; common name; species name; FAO; haul (Kg); units (Ind); storage method (fresh); storage method (frozen); storage method (salted); storage method (loin); storage method (boiled). The operational data can be used to estimate catch per unit effort (CPUE) of the fisheries and socioeconomics of the fisheries including associated cost.

County Parks

Patents by Connecticut Inventors 1800-1890

Connecticut Patents 1800-1890 This list was compiled by Museum of Connecticut History staff in the 1990s, and lists all patents by Connecticut inventors between the years of 1800-1890. This period spans a time of incredible industrial growth and inventiveness in Connecticut, and the Yankee ingenuity on display in these patents helped make the state one of the premier industrial centers of the nation and the world. Many of the pre-1836 patents listed here are only known because of annual lists of patents or patent digests that were published by the Patent Office. The actual records were destroyed in a fire in 1836, and many were never reconstructed. All of the pre-1836 patents are known as the “X-Patents,” and those that have been recovered were given patent numbers beginning with the letter X. Patents up to this time had not actually had numbers of any kind, they were simply known by date and title. About five months before the fire, the Patent Office began numbering their patents; this system, now up to seven digits, is still in use today. Patents found in this dataset can be found using the <a href=”https://www.uspto.gov/patents/search/patent-public-search”>Patent Public Search tool</A> on the U.S. Patent Office’s website. The easiest way to locate a patent is to enter the seven-digit serial number into the basic search. The Connecticut Patents 1800-1890 dataset contains names of inventors, assignees if relevant (inventors could “assign” ownership of patents to another person or entity), descriptions of the invention, patent numbers (if available), and date of issue. It also contains a two-digit class code that corresponds to a general subject area. The subjects are: 01 Firearms, guns, cannons, etc. 02 Metallurgy, metalworking, etc. 03 Woodworking, sawmills, etc. 04 Weaving, sewing, looms, etc. 05 Steam boilers, engines 06 Railroads 07 Ships, boats, canals 08 Clothing 09 Agriculture 10 Hardware, tools, etc. 11 Tanning 12 Rubber 13 Musical instruments 14 Medical 15 Foods and cooking 16 Business and labor 17 Clocks 18 Fireplaces, stoves, furnaces, etc. 19 Lanterns, lamps, and lighting 20 Furniture 21 Household items 22 Doors, windows, drawers, trunks, etc. 23 Grinding mills 24 Stonemasonry, mining, etc. 25 Vehicles, non-motorized 26 Chemical processes? Explosives, distilling, paintmaking, etc. 27 Plumbing, pipes, hoses, etc. and water-powered devices 28 Printing, bookmaking, and paper 29 Engines, coolers, elevators, pneumatics, etc. 30 Ivory 31 Military equipment (non-weapons) 32 Sewing machines 33 Toys, games, and leisure (includes bicycles) 34 Equipment for horses 35 Photography 36 Glassware 37 [doesn't exist] 38 Electricity and electronics 39 Telephones 40 Fire safety 41 Construction 42 School equipment 43 Art

PREDICT Site/Event Characterization

Describes the location, site characteristics and observations made during a visit to a site during the specified time.

Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information: Section 3

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the third spreadsheet of three in the Ethiopia Pastoralist Areas Resilience Improvement and Market Expansion (PRIME) Project IE--Household Information.

Feed the Future-Ethiopia PRIME-Interim Survey-October 2015 through October 2016

This dataset is the second of two interim surveys administered from October 2015 through October 2016 to enable the Feed the Future PRIME project in Ethiopia to monitor program performance by reviewing changes in a number of standardized indicators. These indicators reflect data collected through population-based surveys (PBS) in the geographic areas targeted by Feed the Future interventions, known as the Feed the Future Zones of Influence (ZOI). Each survey was administered to a sample of over 400 households in 17 kebeles (communities) once a month over a 6-month period creating for a total of six rounds of data for each survey.

Feed the Future-Ethiopia PRIME-Interim Survey-October 2014 through April 2015

This dataset is the first of two interim surveys administered from October 2014 through April 2015 to enable the Feed the Future PRIME project in Ethiopia to monitor program performance by reviewing changes in a number of standardized indicators. These indicators reflect data collected through population-based surveys (PBS) in the geographic areas targeted by Feed the Future interventions, known as the Feed the Future Zones of Influence (ZOI). Each survey was administered to a sample of over 400 households in 17 kebeles (communities) once a month over a 6-month period creating for a total of six rounds of data for each survey.