This study employed an extensive literature review to identify commonalities in the data retrieval practices of users of observational data. This dataset consists of a BibTeX file with the 146 bibliographic references examined in:Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A., & Wyatt, S. (2017). Searching Data: A Review of Observational Data Retrieval Practices. arxiv:1707.06937. [cs.DL]The body of literature in the dataset was retrieved using different combinations of keyword searches, primarily in the Scopus database, across all fields. Keyword searches related to information retrieval (e.g. user behavior, information seeking, information retrieval) and data practices (e.g. research practices, community practices, data sharing, data reuse) were combined with keyword searches for research data. As the terms “data” and “search” are ubiquitous in academic literature, title searches also were employed and combined with the controlled vocabulary of the database to locate relevant information. Searches in Scopus included strings such as:KEY ( user AND information ) AND TITLE-ABS-KEY ("research data" OR ( scien W/1 data ) OR ( data W/1 ( repositor OR archive ) ) )TITLE ( data W/0 ( search OR retriev OR discover OR access OR sharing OR reus* ) )AND ( LIMIT-TO ( EXACTKEYWORD , "Information Retrieval" ) OR LIMIT-TO ( EXACTKEYWORD , "Data Retrieval" ) OR LIMIT-TO ( EXACTKEYWORD , "Data Reuse" ) )Bibliometric techniques such as citation chaining and related records were also applied. Pertinent journals and conference proceedings not indexed within Scopus (e.g. the International Journal of Digital Curation) were searched directly using similar keywords.The approximately 400 retrieved documents were examined by close reading to identify articles referring to observational data for inclusion in the final dataset.AcknowledgementsThis work has funded by the NWO Grant 652.001.002 (programme Creative Industrie - Thematisch Onderzoek (CI-TO), Re-SEARCH: Contextual Search for Scientific Research Data)

Google Search Trends: Online Training: Udemy data was reported at 7.000 Score in 20 Mar 2025. This records an increase from the previous number of 0.000 Score for 19 Mar 2025. Google Search Trends: Online Training: Udemy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 20 Mar 2025, with 1206 observations. The data reached an all-time high of 100.000 Score in 10 Aug 2024 and a record low of 0.000 Score in 19 Mar 2025. Google Search Trends: Online Training: Udemy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Laos – Table LA.Google.GT: Google Search Trends: by Categories.

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.

This dataset is comprised of a collection of example DMPs from a wide array of fields; obtained from a number of different sources outlined below. Data included/extracted from the examples include the discipline and field of study, author, institutional affiliation and funding information, location, date created, title, research and data-type, description of project, link to the DMP, and where possible external links to related publications or grant pages. This CSV document serves as the content for a McMaster Data Management Plan (DMP) Database as part of the Research Data Management (RDM) Services website, located at https://u.mcmaster.ca/dmps. Other universities and organizations are encouraged to link to the DMP Database or use this dataset as the content for their own DMP Database. This dataset will be updated regularly to include new additions and will be versioned as such. We are gathering submissions at https://u.mcmaster.ca/submit-a-dmp to continue to expand the collection.

The USDA Nematode Collection is one of the largest and most valuable nematode collections in existence. It contains over 49,000 permanent slides and vials, with a total repository of nematode specimens reaching several million, including Cobb-Steiner, Thorne, and other valuable collections. Nematodes contained in this collection originate from world-wide sources. The USDA Nematode Collection Database contains over 38,000 species entries. A broad range of data is stored for each specimen, including species, host, origin, collector, date collected and date received. All records are searchable and available to the public through the online database. The physical collection is housed at the USDA Nematology Laboratory in Beltsville, MD. Specimens are available for loan to scientists who cannot personally visit the collection. Please see the Policy for Loaning USDANC Specimens for more information on this process. Scientists and other workers are always welcomed and encouraged to deposit material into the collection. Resources in this dataset:Resource Title: USDA Nematode Collection Database. File Name: Web Page, url: https://nt.ars-grin.gov/nematodes/search.cfm The database portal for this collection

Nowadays web portals play an essential role in searching and retrieving information in the several fields of knowledge: they are ever more technologically advanced and designed for supporting the storage of a huge amount of information in natural language originating from the queries launched by users worldwide.A good example is given by the WorldWideScience search engine:The database is available at . It is based on a similar gateway, Science.gov, which is the major path to U.S. government science information, as it pulls together Web-based resources from various agencies. The information in the database is intended to be of high quality and authority, as well as the most current available from the participating countries in the Alliance, so users will find that the results will be more refined than those from a general search of Google. It covers the fields of medicine, agriculture, the environment, and energy, as well as basic sciences. Most of the information may be obtained free of charge (the database itself may be used free of charge) and is considered ‘‘open domain.’’ As of this writing, there are about 60 countries participating in WorldWideScience.org, providing access to 50+databases and information portals. Not all content is in English. (Bronson, 2009)Given this scenario, we focused on building a corpus constituted by the query logs registered by the GreyGuide: Repository and Portal to Good Practices and Resources in Grey Literature and received by the WorldWideScience.org (The Global Science Gateway) portal: the aim is to retrieve information related to social media which as of today represent a considerable source of data more and more widely used for research ends.This project includes eight months of query logs registered between July 2017 and February 2018 for a total of 445,827 queries. The analysis mainly concentrates on the semantics of the queries received from the portal clients: it is a process of information retrieval from a rich digital catalogue whose language is dynamic, is evolving and follows – as well as reflects – the cultural changes of our modern society.

Use this search engine to generate custom tables of orbital and/or physical parameters for all asteroids and comets (or a specified sub-set) in our small-body database. If this is your first time here, you may find it helpful to read our tutorial. Otherwise, simply follow the steps in each section: 'Search Constraints', 'Output Fields', and finally 'Format Options'. If you want details for a single object, use the Small Body Browser instead.

The Washington State Department of Health presents this information as a service to the public. True and correct copies of legal disciplinary actions taken after July 1998 are available on our Provider Credential Search site. These records are considered certified by the Department of Health.

This includes information on health care providers.

Please contact our Customer Service Center at 360-236-4700 for information about actions before July 1998. The information on this site comes directly from our database and is updated daily at 10:00 a.m.. This data is a primary source for verification of credentials and is extracted from the primary database at 2:00 a.m. daily.

News releases about disciplinary actions taken against Washington State healthcare providers, agencies or facilities are on the agency's Newsroom webpage.

Disclaimer The absence of information in the Provider Credential Search system doesn't imply any recommendation, endorsement or guarantee of competence of any healthcare professional. The presence of information in this system doesn't imply a provider isn't competent or qualified to practice. The reader is encouraged to carefully evaluate any information found in this data set.

This dataset contains parametric data (epicentre, magnitude, depth, etc) for over one million earthquakes worldwide. The dataset has been compiled gradually over a period of thirty years from original third-party catalogues, and parameters have not been revised by BGS, although erroneous entries have been flagged where found. The dataset is kept in two versions: the complete "master" version, in which all entries for any single earthquake from contributing catalogue are preserved, and the "pruned" version, in which each earthquake is represented by a single entry, selected from the contributing sources according to a hierarchy of preferences. The pruned version, which is intended to be free from duplicate entries for the same event, provides a starting point for studies of seismicity and seismic hazard anywhere in the world.

Java Tool to extrapolate latitude and longitude from US Postal Service database The purpose of this tool is to estimate latitude and longitude from a user inputted zip code. This tool has been useful in collecting latitude and longitude data for users within the US that may not have known their corresponding latitude and longitude information. User Input : The sole input from the user is the zip code. The program searches the database and then displays the corresponding geographical latitude and longitude. This model was developed as an aid to gather latitude and longitude data from user of our other software tools. This model was developed in JAVA, is simple to use, and runs on multiple platforms (e.g. Mac, PC, Sun). Resources in this dataset:Resource Title: Zip Search Version 0.9. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=156&modecode=50-60-05-00 download page

The study aim is to make biocultural information available. Data include local uses of plants and their cultural contexts from the biologically and culturally hyper-diverse island of Borneo. The database has been developed from secondary data extracted from scientific literature. Data include scientific and local plant names, plant parts used and uses divided into 22 use categories and ethnic belonging of informants. The included files represent the database, information on how the information was collected, search string, criteria and categories. Studien avser att göra biokulturell information för Borneo tillgängligt. Data över lokalt användande av växter och dess kulturella kontext från Borneo. Databasen har sammanställts från vetenskaplig litteratur. Data inkluderar vetenskapliga och lokala växtnamn, använda växtdelar och användningsområden indelade i 22 olika kategorier, samt etnisk tillhörighet av informanter. Filerna innefattar datasetet, beskrivning av hur informationen samlats in, söksträng, kriterier och kategoriseringar. Relevant literature was compiled through a literature search in the web of knowledge database via the “topic” search feature including all databases available in the portal using a designated search string. Delimitation of relevance was done by screening of title and abstract by two independent reviewers. Relevant information was extracted from the generated literature. Plant uses were then categorised into one of 22 use categories.Relevant literature was compiled through a literature search in the web of knowledge database via the “topic” search feature including all databases available in the portal using a designated search string. Delimitation of relevance was done by screening of title and abstract by two independent reviewers. Relevant information was extracted from the generated literature. Plant uses were then categorised into one of 22 use categories. Relevant litteratur samlades in genom ett litteratursök i Wed of Science databas via sökning under "topic" och inkluderar alla i portalen tillgängliga databaser med hjälp av en designerad söksträng.Relevant litteratur samlades in genom ett litteratursök i Wed of Science databas via sökning under "topic" och inkluderar alla i portalen tillgängliga databaser med hjälp av en designerad söksträng. OtherOther ÖvrigtÖvrigt Relevant literature was compiled through a literature search in the web of knowledge database via the “topic” search feature including all databases available in the portal using a designated search string. Delimitation of relevance was done by screening of title and abstract by two independent reviewers. relevant information was extracted from the generated literature. plant uses was then categorised into one of 22 use categories.Relevant literature was compiled through a literature search in the web of knowledge database via the “topic” search feature including all databases available in the portal using a designated search string. Delimitation of relevance was done by screening of title and abstract by two independent reviewers. relevant information was extracted from the generated literature. plant uses was then categorised into one of 22 use categories. Relevant litteratur samlades in genom ett litteratursök i Wed of Science databas via sökning under "topic" och inkluderar alla i portalen tillgänliga databaser med hjälp av en designerad söksträng. Avgränsning för relevans gjordes sen genom att titel och abstrakt granskades av två av varandra oberoende granskare. Relevant information från genererade publikationer extraherades sedan till databasen. Växternas användningsområden kategoriserades sedan i 22 olika kategorier.Relevant litteratur samlades in genom ett litteratursök i Wed of Science databas via sökning under "topic" och inkluderar alla i portalen tillgänliga databaser med hjälp av en designerad söksträng. Avgränsning för relevans gjordes sen genom att titel och abstrakt granskades av två av varandra oberoende granskare. Relevant information från genererade publikationer extraherades sedan till databasen. Växternas användningsområden kategoriserades sedan i 22 olika kategorier.

The British Geological Survey has one of the largest databases in the world on the production and trade of minerals. The dataset contains annual production statistics by mass for more than 70 mineral commodities covering the majority of economically important and internationally-traded minerals, metals and mineral-based materials. For each commodity the annual production statistics are recorded for individual countries, grouped by continent. Import and export statistics are also available for years up to 2002. Maintenance of the database is funded by the Science Budget and output is used by government, private industry and others in support of policy, economic analysis and commercial strategy. As far as possible the production data are compiled from primary, official sources. Quality assurance is maintained by participation in such groups as the International Consultative Group on Non-ferrous Metal Statistics. Individual commodity and country tables are available for sale on request.

The Organic INTEGRITY Database is a certified organic operations database that contains up-to-date and accurate information about operations that may and may not sell as organic, deterring fraud, increases supply chain transparency for buyers and sellers, and promotes market visibility for organic operations. Only certified operations can sell, label, or represent products as organic, unless exempt or excluded from certification. The INTEGRITY database improves access to certified organic operation information by giving industry and public users an easier way to search for data with greater precision than the formerly posted Annual Lists of Certified Operations. You can find a certified organic farm or business, or search for an operation with specific characteristics such as:

The status of an operation: Certified, Surrendered, Revoked, or Suspended The scopes for which an operation is certified: Crops, Livestock, Wild Crops, or Handling

The organic commodities and services that operations offer. A new, more structured classification system (sample provided) will help you find more of what you’re looking for and details about the flexible taxonomy can be found in the INTEGRITY Categories and Items list. Resources in this dataset:Resource Title: Organic INTEGRITY Database. File Name: Web Page, url: https://organic.ams.usda.gov/integrity/Default.aspx Find a specific certified organic farm or business, or search for an operation with specific characteristics. Listings come from USDA-Accredited Certifying Agents. Historical Annual Lists of Certified Organic Operations and monthly snapshots of the full data set are available for download on the Data History page. Only certified operations can sell, label or represent products as organic, unless exempt or excluded from certification.

The NHTSA Vehicle Crash Test Database contains engineering data measured during various types of research, the New Car Assessment Program (NCAP), and compliance crash tests. Information in this database refers to the performance and response of vehicles and other structures in impacts. This database is not intended to support general consumer safety issues. For general consumer information please see the NHTSA's information on buying a safer car.

The CottonGen CottonCyc Pathways Database, part of CottonGen, supports searching and browsing the following CottonCyc databases: Cyc pathways for JGI v2.0 G. raimondii D5 genome assembly This Cyc database was constructed using PathwayTools version 20.0 using the gene models from the JGI v2.0 D5 genome assembly of Gossypium raimondii. There has been no manual curation of this Cyc database. Pathway predictions were made using PathwayTools and in-silico v2.1 annotations as provided by JGI. Cyc pathways for CGP-BGI v1.0 G. hirsutum AD1 genome assembly This Cyc database was constructed using PathwayTools version 20.0 using the gene models from the CGP-BGI v1.0 AD1 genome assembly of Gossypium hirsutum. There has been no manual curation of this Cyc database. Pathway predictions were made using PathwayTools and in-silico v1.0 annotations as provided by CGP-BGI. Search parameters include genes, proteins, RNAs, compounds, reactions, pathways, growth media, and BLAST search. Resources in this dataset:Resource Title: Website Pointer to CottonGen CottonCyc Pathways Database. File Name: Web Page, url: http://ptools.cottongen.org/

Google Search Trends: Online Shopping: eBay data was reported at 0.000 Score in 19 Mar 2025. This stayed constant from the previous number of 0.000 Score for 18 Mar 2025. Google Search Trends: Online Shopping: eBay data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 19 Mar 2025, with 1205 observations. The data reached an all-time high of 100.000 Score in 22 Nov 2022 and a record low of 0.000 Score in 19 Mar 2025. Google Search Trends: Online Shopping: eBay data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Burundi – Table BI.Google.GT: Google Search Trends: by Categories.

Porosity and permeability data form part of Geoscience Australia’s Reservoir, Facies and Shows (RESFACS) database, which contains depth-based information regarding porosity and permeability measured or interpreted from core, sidewall core and well-log analysis of rocks intersected by offshore petroleum wells. Porosity and permeability are rock properties related to the number, size, and connectivity of openings in the rock. More specifically, porosity of a rock is a measure of its ability to hold a fluid within pore-spaces and the permeability is a measure of the ease of flow of a fluid through a porous solid. Data entered into the porosity and permeability tables are primarily sourced from the Basic and Interpretive volumes of Well Completion Reports (WCR) provided by the petroleum industry to the Commonwealth under the Offshore Petroleum and Greenhouse Gas Storage Act (OPGGSA) 2006 and the previous Petroleum (submerged Lands) Act (PSLA) 1967. Data is also sourced from sedimentologic evaluations and petrophysical studies by Geoscience Australia and its predecessor organisations, the Australian Geological Survey Organisation (AGSO) and the Bureau of Mineral Resources (BMR), as well as from state and territory geological organisations, and scientific publications. The database structure has evolved over time and will keep changing as different types of relevant data become available and the delivery platform changes. Data hosted within Geoscience Australia’s Oracle petroleum wells database was initially delivered through the Petroleum Wells web page, http://dbforms.ga.gov.au/www/npm.well.search, which is in the process of being decommissioned . The porosity and permeability data will now be available to view and download through the Geoscience Australia Portal Core, https://portal.ga.gov.au/. Use Porosity and Permeability as your search term to find the relevant data.

In addition to respondents’ highest educational qualification, some surveys also collect data on their main field of education. Current measurement practice involves either a closed question with highly aggregated response categories, which are difficult to use for respondents, or an open question, requiring expensive post-coding. Therefore, a measurement tool for fields of education was developed in the SERISS-project in work package 8, Task 8.3. In deliverable D8.9 we provide a database of fields of education and training in 34 languages, including the definition of a search tree interface to facilitate navigation of categories for respondents. All 120 standard categories and classification codes are taken from UNESCO's International Standard Classification of Education for Fields of Education and Training (ISCED-F). For most languages, detailed 3-digit information is available. The database, including a live search feature, is available at the surveycodings website at https://surveycodings.org/articles/codings/fields-of-education. The search tree can be used for respondents’ self-identification of fields of education and training in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.

Discover domain data with our Whois Database query on 2024-08-28. Accurate insights for your research. Explore Whois Data Center for reliable information.

Database search strategy.