High-throughput computational screening of metal-organic frameworks rely on the availability of disorder-free atomic coordinate files which can be used as input to simulation software packages.

CoRE MOF Datasets are derived from Cambridge Structural Database (CSD) and also from the World Wide Web.

This research is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-17ER16362 (Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulations, Machine Learning, and Experiment).

Supplementary data files associated with this study, which takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology shares original data at the highest rate, and physics shares at the lowest rate. Overall, the study finds that only 13% of articles with original data published in 2014 make the data available to others.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

15 Global export shipment records of Core Board with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

The first release of the TGRAIN Core Twitter database.

NOREN, Anders, CSDCO / LacCore, University of Minnesota, 116 Church St SE, Minneapolis, MN 55455

Open Core Data, a collaboration between the Consortium for Ocean Leadership, Continental Scientific Drilling Coordination Office (CSDCO), and the Interdisciplinary Earth Data Alliance (IEDA), aims to be a key linked open data component of drilling and coring data from both continents and oceans. Guided by FAIR principles, Open Core Data will hold data generated at facilities (CSDCO/LacCore and JANUS data from the JOIDES Resolution at the start), provide semantic enhancement to ingested datasets, and standards-based, human- and machine-readable formats for discovery and access through multiple means: simple web browser user interface, programmatic data access, and web services for data systems requiring drilling and coring information (e.g. Neotoma Paleoecology Database, Paleobiology Database, GPlates, MagIC Magnetics Database, National Geothermal Data System, archives such as NOAA and PANGAEA, etc.). This approach is motivated by the recognition that different scientific communities have varying reasons and requirements for access to drilling data. By leveraging the similar structures of drilling and coring data across institutions, Open Core Data can serve multiple communities and institutions for data discovery, access, and distribution, utilizing the best technological resources available, and it can provide a common platform for development of tools for data visualization and other purposes. It is designed to enable future extension and support of additional scientific communities, including polar coring and drilling, and the large marine coring community.

The Common Core of Data Nonfiscal Survey, 1989-90 (CCD 1989-90) is a data collection that is part of the Common Core of Data (CCD) program; program data is available since 1986-1987 at . CCD-Nonfiscal 1989-90 (https://nces.ed.gov/ccd/index.asp) is a cross-sectional survey that collected non-fiscal data about all public schools, public school districts, and state education agencies in the 50 United States, the District of Columbia, and other outlying jurisdictions. The data were supplied by state education agency officials and included basic information and descriptive statistics on public elementary and secondary schools and schooling in general. Key information produced from CCD-Nonfiscal 1989-90 include information that described schools and school districts, including name, address, and phone number; student counts by race/ethnicity, grade and sex and full-time equivalent (FTE) staff counts by labor category.

Metaproteomics has increasingly been applied to study functional changes in the human gut microbiome. And peptide identification is an important step in metaproteomics research. However, the large search space in metaproteomics studies causes significant challenges for peptide identification. Here, we constructed MetaPep, a core peptide database (including both collections of peptide sequences and tandem MS spectra) greatly accelerating the peptide identifications. Raw files from fifteen metaproteomics projects were re-analyzed and the identified peptide-spectrum matches (PSMs) were used to construct the MetaPep database. The constructed MetaPep database achieved rapid and accurate identification of peptides for human gut metaproteomics.

17842 Global import shipment records of Core,radiator with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

Core Database Statistics

Consumer Records: Over 269 million

Email Addresses: Over 160 million (verified and deliverable)

Phone Numbers: Over 76 million (mobile and landline)

Mailing Addresses: Over 116,000,000 (NCOA processed)

Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

Multi-Channel Campaign Applications

Deploy across all major marketing channels:

Email marketing and automation

Social media advertising

Search and display advertising (Google, YouTube)

Direct mail and print campaigns

Telemarketing and SMS campaigns

Programmatic advertising platforms

Data Quality & Sources

Our consumer data aggregates from multiple verified sources:

Public records and government databases

Opt-in subscription services and registrations

Purchase transaction data from retail partners

Survey participation and research studies

Online behavioral data (privacy compliant)

Technical Delivery Options

File Formats: CSV, Excel, JSON, XML formats available

Delivery Methods: Secure FTP, API integration, direct download

Processing: Real-time NCOA, email validation, phone verification

Custom Selections: 1,000+ selectable demographic and behavioral attributes

Minimum Orders: Flexible based on targeting complexity

Unique Value Propositions

Dual Spouse Targeting: Reach both household decision-makers for maximum impact

Cross-Platform Integration: Seamless deployment to major ad platforms

Real-Time Updates: Monthly data refreshes ensure maximum accuracy

Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

Compliance Management: Built-in opt-out and suppression list management

Ideal Customer Profiles

E-commerce retailers seeking customer acquisition

Financial services companies targeting specific demographics

Healthcare organizations with compliant marketing needs

Automotive dealers and service providers

Home improvement and real estate professionals

Insurance companies and agents

Subscription services and SaaS providers

Performance Optimization Features

Lookalike Modeling: Create audiences similar to your best customers

Predictive Scoring: Identify high-value prospects using AI algorithms

Campaign Attribution: Track performance across multiple touchpoints

A/B Testing Support: Split audiences for campaign optimization

Suppression Management: Automatic opt-out and DNC compliance

Pricing & Volume Options

Flexible pricing structures accommodate businesses of all sizes:

Pay-per-record for small campaigns

Volume discounts for large deployments

Subscription models for ongoing campaigns

Custom enterprise pricing for high-volume users

Data Compliance & Privacy

VIA.tools maintains industry-leading compliance standards:

CCPA (California Consumer Privacy Act) compliant

CAN-SPAM Act adherence for email marketing

TCPA compliance for phone and SMS campaigns

Regular privacy audits and data governance reviews

Transparent opt-out and data deletion processes

Getting Started

Our data specialists work with you to:

1. Define your target audience criteria

2. Recommend optimal data selections

3. Provide sample data for testing

4. Configure delivery methods and formats

5. Implement ongoing campaign optimization

Why We Lead the Industry

With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

United States Core PCE Inflation Nowcast: sa: Contribution: Breakeven Inflation Rate: Breakeven Inflation: 5-Year data was reported at 0.000 % in 01 Dec 2025. This stayed constant from the previous number of 0.000 % for 24 Nov 2025. United States Core PCE Inflation Nowcast: sa: Contribution: Breakeven Inflation Rate: Breakeven Inflation: 5-Year data is updated weekly, averaging 0.000 % from Apr 2019 (Median) to 01 Dec 2025, with 349 observations. The data reached an all-time high of 100.000 % in 20 Jan 2025 and a record low of 0.000 % in 01 Dec 2025. United States Core PCE Inflation Nowcast: sa: Contribution: Breakeven Inflation Rate: Breakeven Inflation: 5-Year data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Personal Consumption Expenditure (PCE) Inflation: Core.

This section of the data release includes core and core section information in the format of a comma-separated value (CSV) file (2018LakePowellCoring_CoreSectionInfo.csv). It is Part 2 (of four) in this data release and provides detailed core information. Complete recovery of a core resulted in approximately 3 m of sediment, which was sectioned into lengths not exceeding 1.5 m shipboard. Thus, all cores with >50% recovery contain multiple sections. This CSV includes drillhole, core, and core section identifiers, section lengths, section tops and bottoms, scaled section tops and bottoms, filenames for corresponding core images, and drilling comments. Drillhole information, such as location and total recovery, are outlined in “Part 1 – Drillhole information from the 2018 coring project in Lake Powell, Utah” (2018LakePowellCoring_DrillholeInfo.csv) of this data release. Core logs and spectrophotometry data are available in “Part 3 – Multi-Sensor Core Logger and spectrophotometry logs of sediment cores collected in 2018 from Lake Powell, Utah” (2018LakePowellCoring_CoreLogData.csv). Corresponding core images can be found in “Part 4 – Photographs of sediment cores collected in 2018 from Lake Powell, Utah” (2018LakePowellCoring_CorePhotos.zip). The Lake Powell Coring Project was a USGS research effort, in cooperation with the Utah Department of Environmental Quality, U.S. Bureau of Reclamation, and U.S. National Park Service. In the fall of 2018, hydraulic piston cores targeted sediment that had been deposited in Lake Powell. This large reservoir on the Colorado River in Utah and Arizona was created after the completion of Glen Canyon Dam in 1963. Retrieval and analysis of cores was undertaken in response to the Gold King mine release from the Bonita Peak Mining District in Colorado on August 5, 2015. This event resulted in the containment loss of three-million gallons of mine-impacted waters which flowed from the Animas River into the San Juan River, and ultimately into Lake Powell. Cores were retrieved from 40 holes, totaling nearly 500 m of core, between November 9 and November 30, 2018. At least 17 holes penetrated into the pre-Glen Canyon Dam land surface, typically in the antecedent river channel. Coring was primarily focused on the San Juan River delta, as it is the most likely location to detect Gold King-derived material, though cores were distributed across the reservoir. Full-depth holes, from the sediment top to the pre-Glen Canyon Dam surface, exceed 30 m at the thickest. Shallow holes, particularly in the San Juan River delta region, targeted only the upper 6 m of sediment. At the water-sediment interface of most cores, particularly those nearest the river mouths, an unconsolidated flocculent layer or “slurry” was typically present. Herein it is treated as the uppermost stratigraphic unit of the sediment column and stratigraphy. The area immediately behind the dam was not targeted; the nearest site to Glen Canyon Dam is located approximately 40 miles upriver. The reservoir sediment is primarily composed of thinly laminated muds with varying amounts of sand or silt. Rotary coring tools were used at the bottoms of holes that penetrated the pre-Glen Canyon Dam surface. The material encountered at the bottom of these holes (commonly bedrock, boulders, and coarse sand) could not be penetrated by hydraulic piston core. Recovery percentages of pre-Glen Canyon Dam sediment were not high, but sufficient material exists for characterization of this surface. Upon completion of the coring campaign, all cores were protected from freezing and freighted to the National Lacustrine Core Facility (LacCore) at the University of Minnesota in Minneapolis. There, each core was logged through its casing with a Geotek Multi-Sensor Core Logger-S (MSCL-S) that measured gamma density, volume-normalized magnetic susceptibility, p-wave amplitude and velocity, and electrical resistivity with a loop sensor. The cores were then split and cleaned, imaged with a Geotek Core Imaging System (MSCL-CIS) linescan camera at 10 pixels/mm (254 dpi) and scanned at a 5-cm interval on a Geotek Core Workstation (MSCL-XYZ) with a Konica Minolta CM2600D spectrophotometer for point-sensor magnetic susceptibility and color, relative gloss, and UV characteristics. The spectrophotometer uses a d/8 measuring geometry to collect light from the ultraviolet to infrared range (360-740 nm wavelengths) and provide CIE (Commission Internationale de l'Éclairage) XYZ wavelengths and L*a*b* color indices for each measurement. As the MSCL-S and MSCL-XYZ are separate logs, the respective data do not usually have corresponding analysis depths. All cores, including archive and working halves, are held in curation at the LacCore repository.

The primary purpose of this project is to provide a listing of all local agencies providing free public elementary and secondary education in the United States and its outlying areas (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1980-1981. It permits the educational community to draw statistically valid samples from which state or national estimates can be made and also provides a mailing list of school systems. Significant variables include name, address, county, grade span, size of system, number of schools, and standard metropolitan statistical area (SMSA) designation.

ANIMIDA TASK 2 HYDROCARBON AND METAL CHARACTERIZATION OF SEDIMENT CORES IN THE ANIMIDA STUDY AREA Contract Number:30998-10902 Author:John Brown Pages:182 Size:3544kb

China % of Value Added of Core Industries of Digital Economy: Application of Digital Technology data was reported at 43.600 % in 2023. China % of Value Added of Core Industries of Digital Economy: Application of Digital Technology data is updated yearly, averaging 43.600 % from Dec 2023 (Median) to 2023, with 1 observations. The data reached an all-time high of 43.600 % in 2023 and a record low of 43.600 % in 2023. China % of Value Added of Core Industries of Digital Economy: Application of Digital Technology data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AVA: Value Added of Core Industries of Digital Economy.

The present Dataset containes the data collected for the gEneSys Systematic Literature Review on the nexus between gender and energy transition. Data have been collected from 152 papers published between 2000 and 2023. The publications have been identified through an hoc research query and retrieved from the Web of Science Database.

The dataset inscludes the following variables:

Title of the publication, category of the categorization of Bell et al., 2020 (Political, Economic, Socio-Ecological, Technological).

Cluster in which the publication has been included.

Parts of the publication’s results about the nexus between gender and energy.

Parts of the publication’s text about the gender gap assessed by the publication.

Parts of the publication’s text about the gender gap identified to be bridged by future research.

The type of the gender issue/s addressed by the publication.

The type of the gender issue/s addressed by the publication.

Technology/ies mentioned in the publication.

The name of the country or countries studied by the publication.

World Bank classification of the level of income of the country or countries studied by the publication.

World Bank classification of the region of the country or countries studied by the publication.

Spatial Context (e.g. international, national, inner-country, peri-urban, rural) of the country or countries studied by the publication.

Research method employed in the publication (qualitative, quantitative, mixed).

Specific qualitative, quantitative or mixed method or methods employed in the publication.

Number of observations for the methods used.

Parts of the publication’s text about the policy recommendations elaborated in the publication.

If the publication mentions a pathway.

Year of publication.

Author/s surname and name initial.

Author/s full surnames and names.

Keywords chosen by the author/s.

Abstract of the publication.

Name of the source or journal.

Type of publication.

Category/ies identified by Web of Science.

Publication’s language.

Keywords identified by Web of Science.

Number of references cited by the publication.

Number of times the publication has been cited in Web of Science Core Database.

Number of times the publication has been cited in Web of Science All Databases.

Name of the publisher.

Digital Object Identifier.

Digital Object Identifier link.

Publication’s number of pages.

Web of Science citation index.

Research area or areas of the publication.

Web of Science Unique Identifier.

The Core Based Statistical Area (CBSA) dataset is August 9, 2019, and is part of the USDOT/BTS's National Transportation Atlas Database (NTAD). The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Metropolitan and Micropolitan Statistical Areas are together termed Core Based Statistical Areas (CBSAs) and are defined by the Office of Management and Budget (OMB) and consist of the county or counties or equivalent entities associated with at least one urban core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties containing the core. Categories of CBSAs are: Metropolitan Statistical Areas, based on urbanized areas of 50,000 or more population, and Micropolitan Statistical Areas, based on urban clusters of at least 10,000 population but less than 50,000 population. The CBSAs for the 2010 Census are those defined by OMB and published in December 2009.

Recently, it has become evident that academic research faces issues with the reproducibility of research data. As Core Facilities (CFs) have a central position in the research infrastructure they are able to promote and disseminate good research standards through their users. To identify the most important factors for research quality, we polled 253 CFs across Europe about their practices and analysed in detail the interaction process between CFs and their users, from the first contact to the publication of the results. Although the survey showed that CFs aim to train and advise their users, it highlighted the following areas, the improvement of which would directly increase research quality: 1) motivating users to follow the advice and procedures for best research practice, 2) providing clear guidance on data management practices, 3) improving communication along the whole research process and 4) clearly defining the responsibilities of each party.

China Consumer Price Index (CPI): Core (excl. Food & Energy) data was reported at 100.500 Prev Year=100 in Mar 2025. This records an increase from the previous number of 99.900 Prev Year=100 for Feb 2025. China Consumer Price Index (CPI): Core (excl. Food & Energy) data is updated monthly, averaging 101.200 Prev Year=100 from Jan 2006 (Median) to Mar 2025, with 231 observations. The data reached an all-time high of 102.500 Prev Year=100 in Feb 2018 and a record low of 98.400 Prev Year=100 in Aug 2009. China Consumer Price Index (CPI): Core (excl. Food & Energy) data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.IA: Consumer Price Index: Same Month PY=100.

Key information about Colombia Core CPI Change

• Colombia Core CPI Change was reported at 5.526 % in Oct 2025.
• This records an increase from the previous number of 5.333 % for Sep 2025.
• Colombia Core CPI Change data is updated monthly, averaging 3.035 % from Jan 2000 to Oct 2025, with 310 observations.
• The data reached an all-time high of 10.593 % in Apr 2023 and a record low of 1.117 % in Jan 2021.
• Colombia Core CPI Change data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Core CPI: Y-o-Y Growth: Monthly.