The Conservation Practice Effectiveness Database compiles information on the effectiveness of a suite of conservation practices. This database presents a compilation of data on the effectiveness of innovative practices developed to treat contaminants in surface runoff and tile drainage water from agricultural landscapes. Traditional conservation practices such as no-tillage and conservation crop rotation are included in the database, as well as novel practices such as drainage water management, blind inlets, and denitrification bioreactors. This will be particularly useful to conservation planners seeking new approaches to water quality problems associated with dissolved constituents, such as nitrate or soluble reactive phosphorus (SRP), and for researchers seeking to understand the circumstances in which such practices are most effective. Another novel feature of the database is the presentation of information on how individual conservation practices impact multiple water quality concerns. This information will be critical to enabling conservationists and policy makers to avoid (or at least be aware of) undesirable tradeoffs, whereby great efforts are made to improve water quality related to one resource concern (e.g., sediment) but exacerbate problems related to other concerns (e.g., nitrate or SRP). Finally, we note that the Conservation Practice Effectiveness Database can serve as a source of the soft data needed to calibrate simulation models assessing the potential water quality tradeoffs of conservation practices, including those that are still being developed. This database is updated and refined annually. Resources in this dataset:Resource Title: 2019 Conservation Practice Effectiveness (CoPE) Database. File Name: Conservation_Practice_Effectiveness_2019.xlsxResource Description: This version of the database was published in 2019.

Users can search for model or promising programs related to community health programs and initiatives. Topics include: access to care, health equity, immunization, mental health, primary care, cultural competence, and environmental health. BackgroundThe Model Practice Database is maintained by the National Association of County and City Health Officials (NACCHO). This database allows users to search for model or promising programs related to community health programs and initiatives. Topics include, but are not limited to: access to care, health equity, immunization, mental health, primary care, cultural competence, and environmental health. User FunctionalityUsers can search for model or promising programs by state or category. Users can view details regarding model programs, contact information for the respective program, and a link to the program webpage, if applicable. Data NotesThe program overview, program details (i.e., agency and community roles, innovation, expenditures, implementation, sustainability and lessons learned), and program contact information are provided for each model program. The year in which the program overview was submitted is indicated with the program summary.Most recent program overviews were submitted in 2009. Programs throughout the United States are included.

Sample Library Carpentry SQL lesson database created from the Directory of Open Access Journals (DOAJ) data. The sample SQL database contains tables: articles, journals, languages, licences, and publishers. Previous version of the sample SQL database: Staiger, Christine (2016): LC-articles. figshare. Dataset. https://doi.org/10.6084/m9.figshare.3409471.v3

This data-set includes information about a sample of 8,887 of Open Educational Resources (OERs) from SkillsCommons website. It contains title, description, URL, type, availability date, issued date, subjects, and the availability of following metadata: level, time_required to finish, and accessibility.

This data-set has been used to build a metadata scoring and quality prediction model for OERs.

This database was prepared using a combination of materials that include aerial photographs, topographic maps (1:24,000 and 1:250,000), field notes, and a sample catalog. Our goal was to translate sample collection site locations at Yellowstone National Park and surrounding areas into a GIS database. This was achieved by transferring site locations from aerial photographs and topographic maps into layers in ArcMap. Each field site is located based on field notes describing where a sample was collected. Locations were marked on the photograph or topographic map by a pinhole or dot, respectively, with the corresponding station or site numbers. Station and site numbers were then referenced in the notes to determine the appropriate prefix for the station. Each point on the aerial photograph or topographic map was relocated on the screen in ArcMap, on a digital topographic map, or an aerial photograph. Several samples are present in the field notes and in the catalog but do not correspond to an aerial photograph or could not be found on the topographic maps. These samples are marked with “No” under the LocationFound field and do not have a corresponding point in the SampleSites feature class. Each point represents a field station or collection site with information that was entered into an attributes table (explained in detail in the entity and attribute metadata sections). Tabular information on hand samples, thin sections, and mineral separates were entered by hand. The Samples table includes everything transferred from the paper records and relates to the other tables using the SampleID and to the SampleSites feature class using the SampleSite field.

Age and length frequency data for finfish and invertebrate species collected during commercial fishing vessels. Samples are collected by fisheries reporting specialist from fish dealers in ports along the northwest Atlantic Ocean from Maine to North Carolina.

This data package contains the Physician Quality Reporting System (PQRS), Performance Rates for Individual Eligible Professionals (EP) PQRS, Consumer Assessment of Healthcare Providers and Systems (CAHPS) and Group Practice.

In 1968, the Missouri Geological Survey (MGS) established the Operation Basement program to address three objectives: a) to obtain drill hole and underground mining data relative to the structure and composition of the buried Precambrian basement; b) to expand mapping in the Precambrian outcrop area and conduct research related to Precambrian geology and mineral resources; and c) to eventually publish the results of the first two objectives in the Contribution to Precambrian Geology series (Kisvarsanyi, 1976). The database presented here represents the first of those objectives, and it includes more data that was gathered after the third objective was accomplished. It was originally compiled in close cooperation with exploration and mining companies operating in Missouri, who provided drillhole data, core and rock samples to MGS. These data enabled geologists to study otherwise unexposed basement rocks from a large area of the state for the first time, allowing better classification and understanding of the Precambrian basement across the state. MGS is continuing data collection and database compilation today as information becomes available, furthering our knowledge of the Missouri Precambrian basement. This effort was supported through a cooperative agreement with the Mineral Resource Program of the U.S. Geological Survey. There is no plan to update this Data Release product.

The State Health Practice Database for Research (SHPDR) captures cross-sectional and longitudinal variation in states’ statutes and laws to enable researchers to more effectively perform clinically oriented health economics research, and investigate the diffusion of medical technology and other health services research outcomes of interest.

Databases used for the study entitled: "One-Leg Stance Postural Sway Is Not Benefited by Bicycle Motocross Practice in Elite Riders".

The largest all-payer ambulatory surgery database in the United States, the Healthcare Cost and Utilization Project (HCUP) Nationwide Ambulatory Surgery Sample (NASS) produces national estimates of major ambulatory surgery encounters in hospital-owned facilities. Major ambulatory surgeries are defined as selected major therapeutic procedures that require the use of an operating room, penetrate or break the skin, and involve regional anesthesia, general anesthesia, or sedation to control pain (i.e., surgeries flagged as "narrow" in the HCUP Surgery Flag Software). Unweighted, the NASS contains approximately 9.0 million ambulatory surgery encounters each year and approximately 11.8 million ambulatory surgery procedures. Weighted, it estimates approximately 11.9 million ambulatory surgery encounters and 15.7 million ambulatory surgery procedures.

Sampled from the HCUP State Ambulatory Surgery and Services Databases (SASD) and State Emergency Department Databases (SEDD) in order to capture both planned and emergent major ambulatory surgeries, the NASS can be used to examine selected ambulatory surgery utilization patterns. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The NASS contains clinical and resource-use information that is included in a typical hospital-owned facility record, including patient characteristics, clinical diagnostic and surgical procedure codes, disposition of patients, total charges, facility characteristics, and expected source of payment, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NASS excludes data elements that could directly or indirectly identify individuals, hospitals, or states. The NASS is limited to encounters with at least one in-scope major ambulatory surgery on the record, performed at hospital-owned facilities. Procedures intended primarily for diagnostic purposes are not considered in-scope.

Restricted access data files are available with a data use agreement and brief online security training.

Global service-learning brings students, instructors, and communities together to support learning and community development across borders. In doing so, global service-learning practitioners act at the intersection of two fields: service-learning and international development. Critical scholarship in all three domains has highlighted the tensions inherent in defining and tracking “success” in community development. In response, service-learning and international development have turned considerable attention to documenting project characteristics, also known as best practices or success factors, which support equitable, sustainable community development. This database accompanies the article "Global Service-Learning - A systematic review of principle and practice," which presents a systematic synthesis of these fields’ best practices in the context of global service-learning. We propose 18 guiding principles for project design which aim to support practitioners in creating and maintaining justice-oriented, stakeholder-driven projects. This database contains the necessary reference material to trace the path of our analysis from abstract review to thematic synthesis. It also contains the final results of the thematic synthesis. To respect copyright restrictions, we have not made PDFs of all articles analyzed publicly accessible. Please contact the authors of this database or of the original article if you seek to access one of the articles we reference.

For more information, see: Hawes, J. K., et al. “Global Service-Learning - A Systematic Review of Principle and Practice.” International Journal of Research on Service-Learning and Community Engagement 10, no. 1 (2022).

Comprehensive dataset of 99 General practice attorneys in Norway as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Google data search exercises can be used to practice finding data or statistics on a topic of interest, including using Google's own internal tools and by using advanced operators.

The Biological Sampling Database (BSD) is an Oracle relational database that is maintained at the NMFS Panama City Laboratory and NOAA NMFS Beaufort Laboratory. Data set includes port samples of reef fish species collected from commercial and recreational fishery landings in the U.S. South Atlantic (NC - FL Keys). The data set serves as an inventory of samples stored at the NMFS Beaufort Labor...

Comprehensive dataset of 2,260 General practice attorneys in Brazil as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

We recently revealed significant variability in protein corona characterization across various proteomics facilities, indicating that data sets are not comparable between independent studies. This heterogeneity mainly arises from differences in sample preparation protocols, mass spectrometry workflows, and raw data processing. To address this issue, we developed standardized protocols and unified sample preparation workflows, distributing uniform protein corona digests to several top-performing proteomics centers from our previous study. We also examined the influence of using similar mass spectrometry instruments on data homogeneity and standardized database search parameters and data processing workflows. Our findings reveal a remarkable stepwise improvement in protein corona data uniformity, increasing overlaps in protein identification from 11% to 40% across facilities using similar instruments and through a uniform database search. We identify the key parameters behind data heterogeneity and provide recommendations for designing experiments. Our findings should significantly advance the robustness of protein corona analysis for diagnostic and therapeutics applications.

The classical paradigm of asymptotic theory employed in econometrics presumes that model dimensionality, p, is fixed as sample size, n, tends to inifinity. Is this a plausible meta-model of econometric model building? To investigate this question empirically, several meta-models of cross-sectional wage equation models are estimated and it is concluded that in the wage-equation literature at least that p increases with n roughly like n l/4, while that hypothesis of fixed model dimensionality of the classical asymptotic paradigm is decisively rejected. The recent theoretical literature on large-p asymptotics is then very briefly surveyed, and it is argued that a new paradigm for asymptotic theory has already emerged which explicitly permits p to grow with n. These results offer some guidance to econometric model builders in assessing the validity of standard asymptotic confidence regions and test statistics, and may eventually yield useful correction factors to conventional test procedures when p is non-negligible relative to n.

This second, and updated, version of the data sample (in support the article "Indicators on firm level innovation activities from web scraped data" https://ssrn.com/abstract=3938767) contains data on companies' innovative behavior measured at the firm-level based on web scraped firm-level data derived from medium-high and high-technology companies in the European Union and the United Kingdom. The data are retrieved from individual company websites and contains in total data on 96,921 companies. The data provide information on various aspects of innovation, most significantly the research and development orientation of the company at the company and product level, the company’s collaborative activities, company’s products, and use of standards. In addition to the web scraped data, the dataset aggregates a variety firm-level indicators including patenting activities. In total, the dataset includes 28 variables with unique identifiers which enables connecting to other databases such as financial data.

This survey aims to investigate research data management practices at EPFL and integrate their results into specific academic services. The previous two editions, in collaboration with TU Delft, Cambridge University and Illinois University, were carried out in 2017 and 2019.

The objective of these surveys is to collect information on researchers' habits in terms of management of their research data, as well as to identify their needs for data curation services/support. For this edition of the survey, a particular focus has been given to the ways in which they disseminate data and code.

You can find here a file corresponding to the report, in PDF, highlighting the findings of the survey, plus the file of the underlying data, in CSV, and a file with the graphical representation of such data, in PDF.

For more information about this survey, a description on how the survey might be re-used by other institutions, and RDM services offered by the EPFL Library, please contact researchdata@epfl.ch.