Purpose of data.gov.lv is to gather and to circulate Government institution and Government organization collected data in on place for public use, as this data is valuable for the development of innovations in the state. On this portal datasets can be browsed by category, keywords or institution. The portal is based on open source technologies including CKAN Open data catalogue. Developed add-ons are available at: https://github.com/dpp-dev The Latvian Open Data Portal was created by the European Regional Development Fund co-financed project Nr. 2.2.1.1/16/I/001 "Public Administration Information and Communication Technology Architecture Management System" (PIKTAPS) The Third Action Plan for Open Government Partnership of Latvia is taking an action towards openness, responsibility, publics’ participation and the use of ICT [1] This plan carries out the improvement and implementation of various services in the Internet environment. One of the 12 commitment plans of Latvia is the development of an open-source public data portal. But to fulfill the entire target of 2017-2019 OGP plan Latvia has committed to involve society in the selection of datasets. Consequently, the website has the ability to vote which data should be opened. So far in Latvia many valuable data were not available, since collecting them is a paid service, for that reason, access to re-usable data containing metadata has been difficult. Only a few institutions, on their own initiative, published open data on their websites. In 2013, the European Union (EU) adopted the Directive 2013/37/EU with a view to introducing uniform practices and rules in all Member States for the re-use of public administration information. In Latvia, in 2015, the relevant amendments were incorporated into the Information Disclosure Law. According to the directive, in Latvia the data that is open should be published "on the authority of its own initiative, if it is useful ", which means the voluntary principle in the publication of data and does not promote the general" open by default "compliance with the principle. This portal was opened within the OGP to facilitate the opening of data, of course, with respect to the protection of personal data. Involving society in choosing the datasets to be opened. From this commitment, an open data portal, gains all the groups of the public: Members of the society will not only be able to vote for data sets of interest to them, but also to obtain data without bureaucracy. Government institutions will increase the efficiency of work and improve their image by opening and publishing their data. Entrepreneurs will have more data available that can be used to create new products or services, thus contributing to overall economic growth.

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two provably correct algorithms to solve this problem — (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual disk access for only less than 5% of the observations. To the best of our knowledge, this is the first flexible MTS search algorithm capable of subsequence search on any subset of variables. Moreover, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

The BMDV open data portal mCLOUD offers a Export interface (REST-API) via the data as RDF according to the DCAT-AP.de specification or can be exported as CSV.

Export as DCAT-AP.de in RDF/XML:

Basic path: https://mcloud.de/export/datasets

Export as CSV:

Basic path: https://mcloud.de/export/csv/datasets

Parameters:

The parameters in the requests are based on the parameters in the portal for a remote search (URL).
At the end of a hit page in the portal, the export is always offered. One possibility is to search normally via the portal and then copy the export URL at the end of a page.

Single data record

A single data record can be retrieved by appending the UUID.
E.g. https://mcloud.de/export/datasets/922e436b- 2f0d-42d7-b3f4-528debab8b87
This export is directly available in the mCLOUD in the data record as a "link to the metadata".

Predefined filters:

All data sets added in the last 24 hours:
filter=newdatasets
https://mcloud.de/export/datasets?filter=newdatasets

All data sets that were changed in the last 24 hours (also includes newly added records):
filter=modifieddatasets
https://mcloud.de/export/datasets?filter=modifieddatasets

Paging (default):

pageSize=10 (number of sentences on one page)
page=1 (display first page)
https://mcloud.de/export/datasets?page=1&pageSize=10

Im DCAT-AP.de export always includes navigation information at the beginning:
itemsPerPage (= pageSize parameter)
totalItems (total number)
firstPage (= first page for page parameter)
lastPage (= last page for page parameter)

Search term:

< i>query=Vehicle
https://mcloud.de/export/ datasets?query=Vehicle

Search facet:

aggs=...
The facet is then specified exactly as in the portal request. Please note the coding:
format%3ACSV = type of access "CSV"
categories%3Aroads = category "road"
format%3ACSV%40%40categories%3Aroads = type of access "CSV" AND category "road"

Together:
aggs=format%3ACSV %40%40categories%3Aroads
https ://mcloud.de/export/datasets?aggs=format%3ACSV%40%40categories%3Aroads

Here is the search in the portal, you can use this as a guide:
https://mcloud .de/web/guest/suche/-/results/filter/auto/format%3ACSV%40%40categories%3Aroads/0
At the end of the page there is also the link (as RDF):
https://mcloud.de/export/datasets?page=1&pageSize=1147&sortOrder=desc&sortField=latest&aggs=format%3ACSV%40%40categories%3Aroads

Sorting field:

No information sorted by ID of the data records
sortField=relevance (relevance)
sortField=latest (current)

Sort order:

sortOrder=asc (ascending, default)
sortOrder=desc (descending)

NASA provides a number of lunar samples for display at museums, planetariums, and scientific expositions around the world. Lunar displays are open to the public. This is a database of every location around the planet displaying returned lunar samples from the Apollo missions.

A series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with …Show full descriptionA series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with enhanced capabilities including 3D visualisation, and online analysis tools. The User Guide Video complements the help menu in the portal. The User guide is broken into a series of topics Introduction Toolbar Map layers Multiple Layers Background Layers and Sharing 3D Layers Tools Custom Layers The step by step guides were produced by James Cropper.

Scientists working on the Hawaii Ocean Time-series (HOT) program have been making repeated observations of the hydrography, chemistry and biology of the water column at a station north of Oahu, Hawaii since October 1988. The objective of this research is to provide a comprehensive description of the ocean at a site representative of the North Pacific subtropical gyre. Cruises are made approximately once per month to the deep-water Station ALOHA (A Long-Term Oligotrophic Habitat Assessment) located 100 km north of Oahu, Hawaii. Measurements of the thermohaline structure, water column chemistry, currents, optical properties, primary production, plankton community structure, and rates of particle export are made on each cruise.

In an effort to assist federal, state and local community officials with risk communication efforts and build a support base for hazard mitigation, sustainability, and resilience discussions within their communities, FEMA Region III has developed the Mitigation Mapping Data Portal. This Geographic Portal provides officials with maps, data, tools and resources to easily and effectively discover and then communicate natural hazard risk information to their partners or constituents. FEMA Region III works with a variety of contracted providers and CTP partners who assist in the delivery of Flood Risk Projects or Mapping Projects and other hazard assessment data to Delaware, the District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia. Integration between Federal, State and Local government leaders increases efficiencies and expands success throughout our project delivery areas.

This Special Eurobarometer survey on nature-based solutions (No 444) investigates Europeans’ perceptions of and engagement with nature-based solutions and whether they perceive there to be any significant environmental and urban or socio-economic problems in the area in which they live. #####The results by volumes are distributed as follows: * Volume A: Countries * Volume AA: Groups of countries * Volume A' (AP): Trends * Volume AA' (AAP): Trends of groups of countries * Volume B: EU/socio-demographics * Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: http://www.gesis.org/en/home/

Consider a scenario in which the data owner has some private or sensitive data and wants a data miner to access them for studying important patterns without revealing the sensitive information. Privacy-preserving data mining aims to solve this problem by randomly transforming the data prior to their release to the data miners. Previous works only considered the case of linear data perturbations - additive, multiplicative, or a combination of both - for studying the usefulness of the perturbed output. In this paper, we discuss nonlinear data distortion using potentially nonlinear random data transformation and show how it can be useful for privacy-preserving anomaly detection from sensitive data sets. We develop bounds on the expected accuracy of the nonlinear distortion and also quantify privacy by using standard definitions. The highlight of this approach is to allow a user to control the amount of privacy by varying the degree of nonlinearity. We show how our general transformation can be used for anomaly detection in practice for two specific problem instances: a linear model and a popular nonlinear model using the sigmoid function. We also analyze the proposed nonlinear transformation in full generality and then show that, for specific cases, it is distance preserving. A main contribution of this paper is the discussion between the invertibility of a transformation and privacy preservation and the application of these techniques to outlier detection. The experiments conducted on real-life data sets demonstrate the effectiveness of the approach.

Under Section 21 of the Act, we are not required to provide information in response to a request if it is already reasonably accessible to you. The information you requested is available from web link: https://opendata.nhsbsa.net/dataset/foi-23358 Data for January 2022 and February 2022 A copy of the information is attached. NHS Prescription Services process prescriptions for Pharmacy Contractors, Appliance Contractors, Dispensing Doctors and Personal Administration with information then used to make payments to pharmacists and appliance contractors in England for prescriptions dispensed in primary care settings (other arrangements are in place for making payments to Dispensing Doctors and Personal Administration). This involves processing over 1 billion prescription items and payments totalling over £9 billion each year. The information gathered from this process is then used to provide information on costs and trends in prescribing in England and Wales to over 25,000 registered NHS and Department of Health and Social Care users. Data source Source System - ISP (National MIS Files) Time period January 2022 and February 2022 The month refers to the month of the report. Please note Appliance Contractors data within the MIS Report shows data for the following month. (E.g. MIS Report for January 2022 will show February 2022 Appliance Contractor data) This dataset FOI25450 has 4 files – January and February 2022 MIS Pharmacy and January and February 2022 MIS Appliance Contractor. This report consists of a management information file detailing monthly Community Pharmacy and Appliance Payments by type of payment and contractor account. Payments include all drug costs, fees, patient charges, locally authorised payments, etc. Other details such as the numbers of items dispensed, patient’s charges collected are also included. The management information file reflects the contractor's payment and prescription data associated with the sustainability and transformation partnerships (STPs) structure at the relevant payment date. The data contained within the files can be interpreted correctly by using the ‘MIS Glossary’ available under ‘Management Information Spreadsheet (MIS) Report’ at https://www.nhsbsa.nhs.uk/information-services-portal-isp/isp-report-information . Disclosure Control The data in column METHADONE PAYMT and ADD FEE-2E within the Pharmacy dataset have been removed following Information Governance policy. February 2022 is the latest MIS report that is available Please note that this request and our response is published on our Freedom of Information disclosure log at:

Datasets used in paper: Telesca L. and Z. Czechowski, Fisher–Shannon Investigation of the Effect of Nonlinearity of Discrete Langevin Model on Behavior of Extremes in Generated Time Series, Entropy 2023, 25, 1650.

The dataset shows, with monthly aggregation, the number of resources modified on the open data portal of the municipality of Milan. Changes to each unique resource are only counted once each month. A resource consists of the representation of the data contained in a dataset, typically exposed in one or more downloadable files (possibly in several different formats).

For 12 months, air temperature was measured at a height of 2 m above the ground at the upper forest line in the Tatras. The aim of these studies was to show the relationship between terrain forms (concave and convex) on air temperature. The lowest air temperature value was characteristic of concave terrain forms and in them the upper forest line ran lower than on convex terrain forms.

NHSBSA Prescription Services process prescriptions for Pharmacy Contractors, Appliance Contractors, Dispensing Doctors and Personal Administration with information then used to make payments to pharmacists and appliance contractors in England for prescriptions dispensed in primary care settings (other arrangements are in place for making payments to Dispensing Doctors and Personal Administration). This involves processing over 1 billion prescription items and payments totalling over £9 billion each year. The information gathered from this process is then used to provide information on costs and trends in prescribing in England and Wales to over 25,000 registered NHS and Department of Health and Social Care users. This report consists of a management information file detailing monthly Community Pharmacy and Appliance Payments by type of payment and contractor account. Payments include all drug costs, fees, patient charges, locally authorised payments, etc. Other details such as the numbers of items dispensed, patient’s charges collected are also included. The management information file reflects the contractor's payment and prescription data associated with the sustainability and transformation partnerships (STPs) structure at the relevant payment date. The data contained within the files can be interpreted correctly by using the ‘MIS Glossary’ available under ‘Management Information Spreadsheet (MIS) Report’ at https://www.nhsbsa.nhs.uk/information-services-portal-isp/isp-report-information . The data in column METHADONE PAYMT and ADD FEE-2E within the Pharmacy dataset have been removed following Information Governance policy. Appliance Contractors data within the MIS- Report shows data for the following month. (E.g. MIS-Report for January 19 will show February 19 Appliance Contractor data). There is a list of previous requests and which months we have provided called MIS FOI Requests in IST/Reference – please add new requests and months provided to this.

A public passenger vehicle is a vehicle used for the transportation of passengers for hire by a public chauffeur. This filtered view contains only licensed taxicabs. The dataset of public passenger vehicles on which this view is based includes licensed taxicabs (medallions), liveries, ambulances, medicars, charter-sightseeing buses, horse-drawn carriages, and pedicabs. For more information, please see http://www.cityofchicago.org/city/en/depts/bacp/supp_info/bacppublicvehicles.html.

What is expenditure data?

The Queensland Government works closely with all Queenslanders to build safe, caring and connected communities, create jobs, protect our environment and enhance quality of life for present and future generations.

To help achieve this, a number of grant and assistance programs are open to individuals, small community groups and non-government organisations right across the State.

Funding programs cover a range of service areas and interests from sport, arts, and events to education, environment and Advance Queensland research and innovation initiatives.

Expenditure data reflects amounts paid for these grant/funding and frontline service procurement programs. This is a consolidated dataset that can be used by the public, non-government organisations and Government departments to research the investment the Queensland Government makes across grant/funding programs.

The information is correct at the time of reporting however figures and other details may be subject to change. Budgeted and expenditure amounts may also be subject to variation due to changes in project timing, scope or funding reallocations.

Where individuals have received funding, these details have been aggregated within the broader program, funding categories or location, to maintain privacy.

Data available

Please view the Data Dictionary (see Data and resources) to understand the data attributes, quality and limitations of this data which should all be considered before using this data for any purpose.

Due to program name changes, consolidation of funding into other programs, machinery-of-government changes and refinement in the data fields collected overtime, comparison of figures across different years may be ineffective.

Data ownership

This dataset provides a consolidated view of payments made by all Queensland Government agencies responsible for the administration of grant and funding programs. The data contained within this file is not owned by Queensland Treasury.

To view the data as provided by the data owners, please use the link under Related resources. Any questions regarding the data should be directed to the respective Queensland Government agency responsible for the payment. You can contact the responsible agency via the Contact Us option.

Related resources

• Agency Datasets —Queensland Government Investment Portal (QGIP)

The Global Population Count Grid Time Series Estimates provide a back-cast time series of population grids based on the year 2000 population grid from SEDAC's Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) data set. The grids were created by using rates of population change between decades from the coarser resolution History Database of the Global Environment (HYDE) database to back-cast the GRUMPv1 population count grids. Mismatches between the spatial extent of the HYDE calculated rates and GRUMPv1 population data were resolved via infilling rate cells based on a focal mean of values. Finally, the grids were adjusted so that the population totals for each country equaled the UN World Population Prospects (2008 Revision) estimates for that country for the respective year (1970, 1980, 1990, and 2000). These data do not represent census observations for the years prior to 2000, and therefore can at best be thought of as estimations of the populations in given locations. The population grids are consistent internally within the time series, but are not recommended for use in creating longer time series with any other population grids, including GRUMPv1, Gridded Population of the World, Version 4 (GPWv4), or non-SEDAC developed population grids. These population grids served as an input to SEDAC's Global Estimated Net Migration Grids by Decade: 1970-2000 data set.

There is a completed file for each month. FOI8592 has 2 files (February 2019 and March 2019) Source System – ISP (National MIS Files) NHSBSA Prescription Services process prescriptions for Pharmacy Contractors, Appliance Contractors, Dispensing Doctors and Personal Administration with information then used to make payments to pharmacists and appliance contractors in England for prescriptions dispensed in primary care settings (other arrangements are in place for making payments to Dispensing Doctors and Personal Administration). This involves processing over 1 billion prescription items and payments totalling over £9 billion each year. The information gathered from this process is then used to provide information on costs and trends in prescribing in England and Wales to over 25,000 registered NHS and Department of Health and Social Care users. This report consists of a management information file detailing monthly Community Pharmacy and Appliance Payments by type of payment and contractor account. Payments include all drug costs, fees, patient charges, locally authorised payments, etc. Other details such as the numbers of items dispensed, patient’s charges collected are also included. The management information file reflects the contractor's payment and prescription data associated with the sustainability and transformation partnerships (STPs) structure at the relevant payment date. The data contained within the files can be interpreted correctly by using the ‘MIS Glossary’ available under ‘Management Information Spreadsheet (MIS) Report’ at https://www.nhsbsa.nhs.uk/information-services-portal-isp/isp-report-information . The data in column METHADONE PAYMT and ADD FEE-2E within the Pharmacy dataset have been removed following Information Governance policy. Appliance Contractors data within the MIS- Report shows data for the following month. (E.g. MIS-Report for January 19 will show February 19 Appliance Contractor data). Previous requests and months provided – please add new requests to this.

A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.

For 12 months, air temperature was measured at a height of 2 m above the ground at the upper forest line in the Tatras. The aim of these studies was to show the relationship between terrain forms (concave and convex) on air temperature. The lowest air temperature value was characteristic of concave terrain forms and in them the upper forest line ran lower than on convex terrain forms.