Warning: Large file size (over 1GB). Each monthly data set is large (over 4 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet. Alternatively add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets, can be used. The Microsoft PowerPivot add-on for Excel is available using the link in the 'Related Links' section below. Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it August take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet. What does the data cover? General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): - the total number of items prescribed and dispensed - the total net ingredient cost - the total actual cost - the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices. GP practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation.

Theories of word learning differentially weigh the role of repeated experience with a novel item, leading to internalization of statistical regularities over time, and the learners use of prior knowledge to infer in-the-moment. Bayesian theories suggest both are critical, but which is weighed more heavily depends on how ambiguous the situation is. To examine this interplay and how it relates to memory, we adapted a Bayesian model of learning (Tenanbaum, Kemp, Griffiths, & Goodman, 2011; Xu & Tenanbaum, 2007) to an inferential word learning task of novel animals, as outline in the following article: “Bayesians learn best: an inferred Bayesian model accounts for individual differences in prior knowledge use during word learning.” Briefly, the model used (i) contextual information provided in the task, quantified by collecting norms for how informative each trial was (likelihood) and (ii) participant’s trial selection accuracy (posterior distribution) to (iii) infer their prior distribution, a proxy for their belief before exposure to the contextual information. Trial accuracy data for the word learning task was collected on one day, and free recall and recognition memory of learned animal names was completed the next day. Norms for how informative each trial was to guide correct selection were collected in a single session with a separate group of participants. Primary data include trial informativeness norms and trial accuracy in the task, both of which were used as input for the Bayesian model. The model infers prior distribution shape parameters from task accuracy and trial norms, completed using the Excel add-in Solver. This is also included in the primary dataset. Output of the model were used to mathematically derive measures of central tendency and spread for participants’ inferred prior distributions, included in the Secondary dataset. These values, along with average block accuracy, were regressed for each participant to examine change across the task. Output from these regressions (slope, intercept and error terms) were used in the statistical analyses with memory measures, which can be found in the Secondary data.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This V7 database has been updated to include the Receptor data from Clarence-Moreton assessment team. The relevant tables of ReceptorList and tbl_Receptors and the spatial data of GM_CLM_ReceptorList_pt were added to this version. The Clarence-Moreton Asset database v7 supersedes the previous version of the Asset database only in Receptor relevant tables/ feature class (i.e. ReceptorList, tbl_Receptors and GM_CLM_ReceptorList_pt ). This dataset contains v7 of the Asset database (CLM_asset_database_20150916.mdb), a Geodatabase version for GIS mapping purposes (CLM_asset_database_20150916_GISOnly.gdb), the draft Receptor Register spreadsheet (BA-CLM-CLM-140-ReceptorRegister-V20150916.xlsx), a data dictionary (CLM_asset_database_doc_20150916.doc), and a folder (NRM_DOC) containing documentation associated with the WAIT process as outlined below. Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. All reports received associated with the WAIT process for Clarence-Morton are included in the zip file as part of this dataset. Elements are initially included in the preliminary assets database if they are partly or wholly within the subregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Clarence-Morton subregion are found in the "AssetList" table of the database. In this version of the database M1 and M2 have both been assessed. Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "CLM_asset_database_doc_20150916.doc", located in the zip file as part of this dataset. The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset. Detailed information describing the database structure and content can be found in the document "CLM_asset_database_doc_20150916.doc" located in the zip file. Some of the source data used in the compilation of this dataset is restricted. Dataset History OBJECTID VersionID Date_ Notes 1 1 2/07/2014 Initial database. 2 2 15/08/2014 Initial database with new WSP assets 3 3 9/09/2014 add 87 line assets from early SEQLD WAIT data ; updated NSW RegERiv and GWMP assets, and changed AID (5010 to 5180 to 15010 to 15180) 4 3.1 15/09/2014 " Updated class ""Groundwater-dependent ecosystems"" to ""Groundwater-dependent ecosystem""" 5 4 20/02/2015 Add additional eight datasets from the community consultation and assessment team: QLD RE 11, NSW GDE, QLD Wetland System 100K, QLD GDE Surface Areas, QLD GDE Line, QLD GDE Terrestrial Areas, NGIS QLD Bores and AHGF Network Stream. Turn off National GDE assets 6 5 3/06/2015 As requested by CLM assessment team, those NGIS economic assets AIDs from17009 and 17013 inclusive replace previous NGIS ecological assets (from same QLD NGIS elements) AIDs from16800 and 16803 inclusive. Turn off assets AIDs from16800 and 16803 7 6 6/07/2015 This v6 CLM Asset database includes M2 test results (Does the asset pass the water dependency test? or WDTest ) from Clarence-Moreton assessment project team. 8 6.1 19/08/2015 "(1) Corrected the spelling error of PAE_Region to Clarence-Moreton for all assets and elements (2) (a) Extracted long ( >255 characters) WD rationale for 2 assets in tab "Water-dependent asset register" and 4 assets in tab "Asset list " in 1.30 Excel file (b) recreated in BA-CLM-CLM-130-WaterDependentAssetRegister-AssetList-V20150819.xlsx (3) Modified queries (Find_All_Asset_List and Find_Waterdependent_asset_register) for (2)(a)" 9 7 16/09/2015 "(1)(a) Add table ReceptorList in CLM_asset_database_20150916.mdb, using the Excel file from CLM project team (b) Create draft BA-CLM-CLM-140-ReceptorRegister-V20150916.xlsx (2) Add table tbl_Receptors in CLM_asset_database_20150916.mdb and GM_CLM_ReceptorList_pt in CLM_asset_database_20150916_GISOnly.gdb, using the spatial data from CLM project team; (3)Add SQL query "Find_used_Receptor" for extracting all used receptor for the register" Dataset Citation Bioregional Assessment Programme (2014) Asset database for the Clarence-Moreton bioregion on 16 September 2015. Bioregional Assessment Derived Dataset. Viewed 10 July 2017, http://data.bioregionalassessments.gov.au/dataset/e7940ec8-ec73-4cc5-bc4e-0c85f98354f1. Dataset Ancestors Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements 20131204 Derived From Combined Surface Waterbodies for the Clarence-Moreton bioregion Derived From Queensland QLD - Regional - NRM - Water Asset Information Tool - WAIT - databases Derived From Version 02 Asset list for Clarence Morton 8/8/2014 - ERIN ORIGINAL DATA Derived From Asset database for the Clarence-Moreton bioregion on 11 December 2014, minor version v20150603 Derived From NSW Office of Water Surface Water Entitlements Locations v1_Oct2013 Derived From Geofabric Surface Catchments - V2.1 Derived From Matters of State environmental significance (version 4.1), Queensland Derived From Geofabric Surface Network - V2.1 Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only Derived From Ramsar Wetlands of Australia Derived From National Groundwater Dependent Ecosystems (GDE) Atlas Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores v3 03122014 Derived From Multi-resolution Valley Bottom Flatness MrVBF at three second resolution CSIRO 20000211 Derived From National Groundwater Information System (NGIS) v1.1 Derived From Birds Australia - Important Bird Areas (IBA) 2009 Derived From Geofabric Surface Network - V2.1.1 Derived From Queensland QLD Regional CMA Water Asset Information WAIT tool databases RESTRICTED Includes ALL Reports Derived From Queensland wetland data version 3 - wetland areas. Derived From Multi-resolution Ridge Top Flatness at 3 second resolution CSIRO 20000211 Derived From South East Queensland GDE (draft) Derived From Geofabric Surface Cartography - V2.1 Derived From Version 01 Asset list for Clarence Morton 10/3/2014 - ERIN ORIGINAL DATA Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA) Derived From CLM - 16swo NSW Office of Water Surface Water Offtakes - Clarence Moreton v1 24102013 Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only) Derived From QLD Dept of Natural Resources and Mines, Surface Water Entitlements 131204 Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) Derived From Asset database for the Clarence-Moreton bioregion on 19 August 2015. Derived From CLM - Bore allocations QLD v02 Derived From GEODATA TOPO 250K Series 3 Derived From NSW Catchment Management Authority Boundaries 20130917 Derived From Biodiversity status of pre-clearing and remnant regional ecosystems - South East Qld Derived From Commonwealth Heritage List Spatial Database (CHL) Derived From CLM16swo NSW Office of Water Surface Water Offtakes processed for Clarence Moreton v2 06032014 Derived From CLM16gwl NSW Office of Water, GW licence extract linked to spatial locations in CLM v2 28022014 Derived From Bioregional Assessment areas v03 Derived From Groundwater Bores Without Licence NGIS QLD CLM 20150211 Derived From National Heritage List Spatial Database (NHL) (v2.1) Derived From Asset database for the Clarence-Moreton bioregion on 11 December 2014, minor version v20150220 Derived From Land classification for the Clarence-Moreton preliminary assessment extent Derived From QLD DNRM Licence Locations Linked to Cadastre Plan - v1 - 20140307 Derived From Queensland wetland data version 3 - wetland areas - WETCLASS: E, L, M, P, R Derived From NSW Office of Water combined geodatabase of regulated rivers and water sharing plan regions Derived From CLM16swo NSW Office of Water Surface Water Offtakes processed for Clarence Moreton v3 12032014 Derived From Australia World Heritage Areas Derived From Australia - Present Major Vegetation Groups - NVIS Version 4.1 (Albers 100m analysis product) Derived From Northern Rivers CMA GDEs (DRAFT DPI pre-release) Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases, RESTRICTED Includes ALL Reports Derived From Natural Resource Management (NRM) Regions 2010 Derived From CLM Preliminary Assessment Extent Definition & Report( CLM PAE) Derived From Geological Provinces - Full Extent Derived From New South Wales NSW - Regional - CMA - Water Asset Information Tool - WAIT - databases Derived From Receptors for the Clarence-Moreton subregion Derived From Catchment Scale Land Use of Australia -

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

Have you ever wanted to create a quick thematic map of London but lacked the GIS skills or software to do it yourself?

These free mapping tools from the GLA Intelligence Unit allows the user to input their own data to create an instant map that can be copied over into Word or another application of your choice. The user can also copy over the legend, and add labels.

The template allows the user to select either 4 or 5 ranges, and it even has a function to change the colours on the map (default colours are blue).

The tool now also allows users to input their own ranges, which will override the automatic ranges.

There is: Standard borough thematic map

Borough thematic map for categories (as opposed to numbers).

And ward maps for individual boroughs see list below.

Copyright notice: If you publish these maps, a copyright notice must be included within the report saying: "Contains Ordnance Survey data © Crown copyright and database rights."

Ward maps

Ward mapping tools for each borough have also been created. Select the borough you require from the list below:

All London Wards map with pre-2014 boundaries

Barking and Dagenham, Barnet, Bexley, Brent, Bromley, Camden, Croydon, Ealing, Enfield, Greenwich, Hackney (pre 2014), Hammersmith and Fulham, Haringey, Harrow, Havering, Hillingdon, Hounslow, Islington, Kensington and Chelsea (pre 2014), Kingston upon Thames, Lambeth, Lewisham, Merton, Newham, Redbridge, Richmond upon Thames, Southwark, Sutton, Tower Hamlets (pre 2014), Waltham Forest, Wandsworth, Westminster

New ward boundaries - came into effect from May 2014

All London wards map 2014 including the new ward boundaries for Hackney, Kensington and Chelsea, and Tower Hamlets following changes in May 2014.

Hackney, Kensington and Chelsea, Tower Hamlets

https://londondatastore-upload.s3.amazonaws.com/london-excel-map-thumb.JPG" alt="Alt text">

NOTE: Excel 2003 users must 'ungroup' the map for it to work.

Full instructions are contained within the spreadsheet. If you have any questions about these tools please contact Gareth Piggott.

Macros

The tool works in any version of Excel. But the user MUST ENABLE MACROS, for the features to work. There a some restrictions on functionality in the ward maps in Excel 2003 and earlier - full instructions are included in the spreadsheet.

To check whether the macros are enabled in Excel 2003 click Tools, Macro, Security and change the setting to Medium. Then you have to re-start Excel for the changes to take effect. When Excel starts up a prompt will ask if you want to enable macros - click yes.

In Excel 2007 and later, it should be set by default to the correct setting, but if it has been changed, click on the Windows Office button in the top corner, then Excel options (at the bottom), Trust Centre, Trust Centre Settings, and make sure it is set to 'Disable all macros with notification'. Then when you open the spreadsheet, a prompt labelled 'Options' will appear at the top for you to enable macros.

To create your own thematic borough maps in Excel using the ward map tool as a starting point, read these instructions. You will need to be a confident Excel user, and have access to your boundaries as a picture file from elsewhere. The mapping tools created here are all fully open access with no passwords.

The intention is to collect data for the calendar year 2009 (or the nearest year for which each business keeps its accounts. The survey is considered a one-off survey, although for accurate NAs, such a survey should be conducted at least every five years to enable regular updating of the ratios, etc., needed to adjust the ongoing indicator data (mainly VAGST) to NA concepts. The questionnaire will be drafted by FSD, largely following the previous BAS, updated to current accounting terminology where necessary. The questionnaire will be pilot tested, using some accountants who are likely to complete a number of the forms on behalf of their business clients, and a small sample of businesses. Consultations will also include Ministry of Finance, Ministry of Commerce, Industry and Labour, Central Bank of Samoa (CBS), Samoa Tourism Authority, Chamber of Commerce, and other business associations (hotels, retail, etc.).

The questionnaire will collect a number of items of information about the business ownership, locations at which it operates and each establishment for which detailed data can be provided (in the case of complex businesses), contact information, and other general information needed to clearly identify each unique business. The main body of the questionnaire will collect data on income and expenses, to enable value added to be derived accurately. The questionnaire will also collect data on capital formation, and will contain supplementary pages for relevant industries to collect volume of production data for selected commodities and to collect information to enable an estimate of value added generated by key tourism activities.

The principal user of the data will be FSD which will incorporate the survey data into benchmarks for the NA, mainly on the current published production measure of GDP. The information on capital formation and other relevant data will also be incorporated into the experimental estimates of expenditure on GDP. The supplementary data on volumes of production will be used by FSD to redevelop the industrial production index which has recently been transferred under the SBS from the CBS. The general information about the business ownership, etc., will be used to update the Business Register.

Outputs will be produced in a number of formats, including a printed report containing descriptive information of the survey design, data tables, and analysis of the results. The report will also be made available on the SBS website in “.pdf” format, and the tables will be available on the SBS website in excel tables. Data by region may also be produced, although at a higher level of aggregation than the national data. All data will be fully confidentialised, to protect the anonymity of all respondents. Consideration may also be made to provide, for selected analytical users, confidentialised unit record files (CURFs).

A high level of accuracy is needed because the principal purpose of the survey is to develop revised benchmarks for the NA. The initial plan was that the survey will be conducted as a stratified sample survey, with full enumeration of large establishments and a sample of the remainder.

v01: This is the first version of the documentation. Basic raw data, obtained from data entry.

The scope of the 2009 BAS is all employing businesses in the private sector other than those involved in agricultural activities.

Included are:
· Non-governmental organizations (NGOs, not-for profit organizations, etc.);
· Government Public Bodies

Excluded are:
· Non-employing units (e.g., market sellers);
· Government ministries, constitutional offices and those public bodies involved in public administration and included in the Central Government Budget Sector;
· Agricultural units (unless large scale/commercial - if the Agriculture census only covers household activities);
· “Non-resident” bodies such as international agencies, diplomatic missions (e.g., high commissions and embassies, UNDP, FAO, WHO);

The survey coverage is of all businesses in scope as defined above. Statistical units relevant to the survey are the enterprise and the establishment. The enterprise is an institutional unit and generally corresponds to legal entities such as a company, cooperative, partnership or sole proprietorship. The establishment is an institutional unit or part of an institutional unit, which engages in one, or predominantly one, type of economic activity. Sufficient data must be available to derive or meaningfully estimate value added in order to recognize an establishment. The main statistical unit from which data will be collected in the survey is the establishment. For most businesses there will be a one-to-one relationship between the enterprise and the establishment, i.e., simple enterprises will comprise only one establishment. The purpose of collecting data from establishments (rather than from enterprises) is to enable the most accurate industry estimates of value added possible.

• Collection start: 2009
• Collection end: 2009

[Note: Integrated as part of FoodData Central, April 2019.] The database consists of several sets of data: food descriptions, nutrients, weights and measures, footnotes, and sources of data. The Nutrient Data file contains mean nutrient values per 100 g of the edible portion of food, along with fields to further describe the mean value. Information is provided on household measures for food items. Weights are given for edible material without refuse. Footnotes are provided for a few items where information about food description, weights and measures, or nutrient values could not be accommodated in existing fields. Data have been compiled from published and unpublished sources. Published data sources include the scientific literature. Unpublished data include those obtained from the food industry, other government agencies, and research conducted under contracts initiated by USDA’s Agricultural Research Service (ARS). Updated data have been published electronically on the USDA Nutrient Data Laboratory (NDL) web site since 1992. Standard Reference (SR) 28 includes composition data for all the food groups and nutrients published in the 21 volumes of "Agriculture Handbook 8" (US Department of Agriculture 1976-92), and its four supplements (US Department of Agriculture 1990-93), which superseded the 1963 edition (Watt and Merrill, 1963). SR28 supersedes all previous releases, including the printed versions, in the event of any differences. Attribution for photos: Photo 1: k7246-9 Copyright free, public domain photo by Scott Bauer Photo 2: k8234-2 Copyright free, public domain photo by Scott Bauer Resources in this dataset:Resource Title: READ ME - Documentation and User Guide - Composition of Foods Raw, Processed, Prepared - USDA National Nutrient Database for Standard Reference, Release 28. File Name: sr28_doc.pdfResource Software Recommended: Adobe Acrobat Reader,url: http://www.adobe.com/prodindex/acrobat/readstep.html Resource Title: ASCII (6.0Mb; ISO/IEC 8859-1). File Name: sr28asc.zipResource Description: Delimited file suitable for importing into many programs. The tables are organized in a relational format, and can be used with a relational database management system (RDBMS), which will allow you to form your own queries and generate custom reports.Resource Title: ACCESS (25.2Mb). File Name: sr28db.zipResource Description: This file contains the SR28 data imported into a Microsoft Access (2007 or later) database. It includes relationships between files and a few sample queries and reports.Resource Title: ASCII (Abbreviated; 1.1Mb; ISO/IEC 8859-1). File Name: sr28abbr.zipResource Description: Delimited file suitable for importing into many programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Title: Excel (Abbreviated; 2.9Mb). File Name: sr28abxl.zipResource Description: For use with Microsoft Excel (2007 or later), but can also be used by many other spreadsheet programs. This file contains data for all food items in SR28, but not all nutrient values--starch, fluoride, betaine, vitamin D2 and D3, added vitamin E, added vitamin B12, alcohol, caffeine, theobromine, phytosterols, individual amino acids, individual fatty acids, or individual sugars are not included. These data are presented per 100 grams, edible portion. Up to two household measures are also provided, allowing the user to calculate the values per household measure, if desired.Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/ Resource Title: ASCII (Update Files; 1.1Mb; ISO/IEC 8859-1). File Name: sr28upd.zipResource Description: Update Files - Contains updates for those users who have loaded Release 27 into their own programs and wish to do their own updates. These files contain the updates between SR27 and SR28. Delimited file suitable for import into many programs.

The JNCC River Macrophytes Database (RMD) is a Microsoft Access database constructed to house data on the plant communities of rivers in Great Britain and Northern Ireland. An extract in Excel format is also provided. The RMD includes data from over 7,000 survey sites and is the most comprehensive database of its kind. Data have been collected from all over the UK between 1977 and the present day, following the methods of Holmes et al. (1999). The macrophyte survey method records aquatic and marginal plants in a 500 m-long survey section of river. Species from the river channel and the margins/base of the bank are recorded separately on a three-point scale of relative abundance and percentage cover. A standard check-list of species is used to aid recording. The field data can be used to classify the plant community as described by Holmes et al. (1999), and the database has a facility that allows keying-out of the community to sub-type level. This plant community classification has been used as the basis of river SSSI selection (see chapter 6 of Guidelines for Selection of Biological SSSIs). The database also holds a small amount of fish data. The RMD is an ‘active’ database (i.e. survey records can still be added). However, with a new standard method of river plant survey now being adopted by the UK conservation agencies (i.e. the LEAFPACS method), it is likely that less surveys will be added in future, and it may develop into more of a 'legacy' database. In 2011 the RMD was made available through the JNCC website with some restrictions on re-use. In June 2018, JNCC re-published the RMD as open data under the Open Government Licence. In November 2019 the invertebrate survey records were removed whilst some of these records underwent further validity checks. Background information on the classification system: Holmes, N.T, Boon, P.J., & Rowell, T.A. Vegetation communities of British rivers - a revised classification (1999) Link to the Vegetation communities of British rivers on the JNCC Resource hub: https://hub.jncc.gov.uk/assets/a974944a-3cd4-4574-9c1a-c977d482c0ed

The Census of Agriculture is a complete count of U.S. farms and ranches and the people who operate them. Even small plots of land - whether rural or urban - growing fruit, vegetables or some food animals count if $1,000 or more of such products were raised and sold, or normally would have been sold, during the Census year. The Census of Agriculture, taken only once every five years, looks at land use and ownership, operator characteristics, production practices, income and expenditures. For America's farmers and ranchers, the Census of Agriculture is their voice, their future, and their opportunity. The Census Data Query Tool (CDQT) is a web-based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. The data found via the CDQT may also be accessed in the NASS Quick Stats database. The CDQT is unique in that it automatically displays data from the past five Census of Agriculture publications. The CDQT is presented as a "2017 centric" view of the Census of Agriculture data. All data series that are present in the 2017 dataset are available within the CDQT, and any matching data series from prior Census years will also display (back to 1997). If a data series is not included in the 2017 dataset, then data cells will remain blank in the tool. For example, one of the data series had a label change from "Operator" to "Producer." This means that data from prior Census years labelled "Operator" will not show up where the label has changed to “Producer” for 2017. The new Census Data Query Tool application can be used to query Census data from 1997 through 2017. Data are searchable by Census table and are downloadable as CSV or PDF files. 2017 Census Ag Atlas Maps are also available for download. Resources in this dataset:Resource Title: 2017 Census of Agriculture - Census Data Query Tool (CDQT). File Name: Web Page, url: https://www.nass.usda.gov/Quick_Stats/CDQT/chapter/1/table/1 The Census Data Query Tool (CDQT) is a web based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. The data found via the CDQT may also be accessed in the NASS Quick Stats database. The CDQT is unique in that it automatically displays data from the past five Census of Agriculture publications. The CDQT is presented as a "2017 centric" view of the Census of Agriculture data. All data series that are present in the 2017 dataset are available within the CDQT, and any matching data series from prior Census years will also display (back to 1997). If a data series is not included in the 2017 dataset, then data cells will remain blank in the tool. For example, one of the data series had a label change from "Operator" to "Producer." This means that data from prior Census years labelled "Operator" will not show up where the label has changed to "Producer" for 2017. Using CDQT:

Upon entering the CDQT, a data table is present. Changing the parameters at the top of the data table will retrieve different combinations of Census Chapter, Table, State, or County (when selecting Chapter 2). For the U.S., Volume 1, US/State Chapter 1 will include only U.S. data; Chapter 2 will include U.S. and State level data. For a State, Volume 1 US/State Level Data Chapter 1 will include only the State level data; Chapter 2 will include the State and county level data. Once a selection is made, press the “Update Grid” button to retrieve the new data table. Comma-separated values (CSV) download, compatible with most spreadsheet and database applications: to download a CSV file of the data as it is currently presented in the data grid, press the "CSV" button in the "Export Data" section of the toolbar. When CSV is chosen, data will be downloaded as numeric. To view the source PDF file for the data table, press the "View PDF" button in the toolbar.

Published: 25th February 2020 - The NHSBSA ‘One Drug Database’ project is underway to provide a consistent, single source of prescriptions information. The first release of new data was due in February 2020 (December 2019 data) on the NHSBSA website, however this has been delayed a month. As a result this is an additional and FINAL release of PLP data by NHS Digital. This means that from March 2020 the PLP data will ONLY be available from the NHSBSA website. There will also be differences in the way data is presented. You can read more about the project, and how this affects the NHSBSA systems and reports in the related link at the bottom of this web page. Practice level prescribing data is a list of all medicines, dressings and appliances that are prescribed by all practices in England and dispensed in the community each month. A zip file is available which users are able to download and extract all 3 files locally. What does the data cover? Practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, including GP practices, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): the total number of items prescribed and dispensed the total net ingredient cost the total actual cost the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to practices. Practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation. Warning: Large file size (over 1GB). Each monthly data set is large (over 10 million rows), but can be viewed using add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets. The Microsoft PowerPivot add-on for Excel is available using the link in the 'Related Links' section below. Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet.

Published: 07 September 2018 - Practice level prescribing data is a list of all medicines, dressings and appliances that are prescribed by all practices in England and dispensed in the community each month. From July 2016 this data has been published on the 1st Friday of the month. The July 2018 data will be published on Friday 5 October 2018. What does the data cover? Practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, including GP practices, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): the total number of items prescribed and dispensed the total net ingredient cost the total actual cost the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to practices. Practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation. Warning: Large file size (over 1GB). Each monthly data set is large (over 10 million rows), but can be viewed using add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets. The Microsoft PowerPivot add-on for Excel is available using the link in the 'Related Links' section below. Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet.

Following a review of our processes, NHS Digital has recently decided to bring forward the publishing date for Practice level Prescribing data. This data is currently published on the 1st Friday of the month. The January 2017 data will be published on Friday 7 April 2017, however these dates are constantly under review and may move earlier. What does the data cover? General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): - the total number of items prescribed and dispensed - the total net ingredient cost - the total actual cost - the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices. GP practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation. Warning: Large file size (over 1GB). Each monthly data set is large (over 10 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet. Alternatively add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets, can be used. The Microsoft PowerPivot add-on for Excel is available using the link in the 'Related Links' section below. Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet.