Google dataset search pdf Continue Across the Internet, there are millions of data sets about just about any subject that interests you. If you want to buy a puppy, you can find datasets, compiling complaints from puppy buyers or research on puppy cognition. Or, if you like skiing, you can find data on the income of ski resorts or injuries and participation numbers. Dataset Search has indexed nearly 25 million of these datasets, giving you a single place to search for datasets and find links to where the data is. Over the past year, people have tried it and provided feedback, and now Dataset Search is officially out of beta. Some search results for the ski query, which include datasets ranging from the speeds of the fastest skiers to the income of ski resorts. Based on what we learned from the first Dataset Search users, we've added new features. You can now filter results based on the types of dataset you want (such as tables, images, text), or the dataset is available for free from the vendor. If you're a geographic area dataset, you can see the map. In addition, the product is now available on a mobile phone, and we have significantly improved the quality of the description of the datasets. However, one thing hasn't changed: anyone who publishes data can make their datasets detectable in Dataset Search using an open standard (schema.org) to describe the properties of their dataset on their own web page. We also learned how many different types of people are looking for data. There are scientific researchers who find data to develop their hypotheses (for example, try oxytocin), students are looking for free data in table format covering the topic of their senior thesis (for example, try incarceration with appropriate filters), business analysts and data scientists looking for information about mobile applications or fast food establishments, and so on. There's data on all of this! And what do our users ask? The most common requests include education, weather, cancer, crime, football, and, yes, dogs. Some search results to request a fast food outlet. Dataset Search also gives us a snapshot of the data there on the internet. Here are some highlights. The largest topics covering datasets are geosciences, biology and agriculture. Most governments around the world publish their data and describe it through schema.org. The United States leads the way in the number of publicly available government data sets, with more than 2 million. And the most popular data formats? Tables- you can find more than 6 million of them on Dataset Search.The number of datasets that can be found in Dataset Search continues to grow. If you have a data set on your website and you have described it using a schema.org open others may find it in Dataset Search. If you know that a dataset exists but you can't find it in your search for a dataset, ask the vendor to add schema.org schema.org and others will be able to learn about their dataset as well. Dataset Search is out of beta, but we will continue to improve the product regardless of whether it has a beta next to it. If you haven't already, take Dataset Search Spin, and tell us what you think. Espanyol (Latinoamerica) Please enter the term search. Datasets are easier to find when you provide supporting information such as their name, description, creator, and distribution formats as structured data. Google's approach to dataset detection uses schema.org standards and other metadata that can be added to pages when describing datasets. The purpose of this markup is to improve the detection of data sets from areas such as life science, social science, machine learning, civil and government data, and more. Datasets can be found using the dataset search tool. Here are some examples of what might qualify as a data set: a table or CSV file with some data Organized collection of file tables in a proprietary format that contains data Collection files that together make up some meaningful data set structured object with data in a different format, which you can download into a special tool for processing images of capture of data files related to machine learning, such as trained parameters or definition of the structure of the neural network All what looks like a dataset for you How to add structured data Structured data is a standardized format for providing information about the page and classifying the contents of the page. If you're not ready for structured data, you can learn more about how structured data works. Here's an overview of how to create, test, and release structured data. For a step-by-step guide on how to add structured data to a web page, check out the structured data lab code lab. Removing a dataset from dataset search results If you don't want the dataset to be published in Dataset search results, use the robot meta tag to manage the dataset index. Keep in mind that it may take some time (days or weeks, depending on the scan schedule) for changes to be reflected on Dataset Search. Our approach to dataset detection We can understand structured data on web pages about datasets using either schema.org Dataset markups or equivalent structures presented in W3C in the Vocabulary data catalog (DCAT) format. We are also studying the experimental support for structured data based on W3C CSVW, and look forward to the evolution and adaptation of our approach as best practice emerges to describe the data set. For For more information on our approach to detecting datasets, see Examples of datasets using JSON-LD and schema.org (preferably) in the rich results test. The same schema.org vocabulary can also be used in RDFa 1.1 or Microdata syntaxes. You can also use the W3C DCAT dictionary to describe metadata. The next example is на реальном описании набора данных. JSON-LD Вот пример набора данных в JSON-LD: <html><head><title>База данных о событиях шторма NCDC</title><script type=application/ld+json> { @context: @type:Dataset, name:NCDC Storm Events Database, description:Storm Data is provided by the National Weather Service (NWS) and contain statistics on..., url: sameAs: identifier: [ /12345/fk1234], keywords:[ ATMOSPHERE > ATMOSPHERIC PHENOMENA > CYCLONES, ATMOSPHERE > ATMOSPHERIC PHENOMENA > DROUGHT, ATMOSPHERE > ATMOSPHERIC PHENOMENA > FOG, ATMOSPHERE > ATMOSPHERIC PHENOMENA > FREEZE ], license : hasPart : [ { @type: Dataset, name: Sub dataset 01, description : Informative description of the first subdataset..., license : }, { @type: Dataset, name: Sub dataset 02, description: Informative description of the second subdataset..., license : } ], creator:{ @type:Organization, url: name:OC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce, contactPoint:{ @type:ContactPoint, contactType: customer service, telephone:+1-828-271-4800, email:[email protected] } }, includedInDataCatalog:{ @type:DataCatalog, name:data.gov }, distribution:[ { @type:DataDownload, encodingFormat:CSV, contentUrl: }, { @type:DataDownload, encodingFormat:XML, contentUrl: } ], temporalCoverage:1950-01-01/2013-12-18, spatialCoverage:{ @type:Place, geo:{ @type:GeoShape, box:18.0 -65.0 72.0 172.0 } } } </script></head><body></body></html>RDFa Вот пример набора данных в RDFa с использованием словаря DCAT : Consolidated_Statement_of_Cash_Flows_en.csv'lt;rel'dcat:distribution href'files/Consolidated_Statement_of_Cash_Flows_en.xls/lt;lt/property span'dType:media content/vnd.ms-excel'gt;Consolidated_Statement_of_Cash_Flows_en.xls'lt; span'gt;'lt;'lt'lt;'lt'lt;'lt'. (consolidated_statement_of_cash_flows_en.xml/span property/dcat:mediaType content/xml'consolidated_statement_of_cash_flows_en.xml'lt; In addition to structured data guidelines, we recommend the following site map and the source and provenance of best practices listed below. Best Practices Sitemap Use sitemap to help Google find URLs. Using sitemap files and sameAs of markup helps document how dataset descriptions are published on your website. If you have a dataset repository, you probably have at least two types of pages: canonical (landing) pages for each data set and pages that list multiple data sets (such as search results or some subsets of datasets). We recommend adding structured data about the dataset to canonical pages. Use the same property to link to a canonical page if you add structured data to multiple copies of the dataset, such as lists on search results pages. Google doesn't need every mention of the same data set to be explicitly marked, but if you do so for other reasons, we strongly recommend using the sameAs. The best methods of raw data are usually published, aggregated, and based on other data sets. This is the initial blueprint for our approach to presenting situations in which the dataset is a copy or otherwise based on another data set. Use the same PropertyAs to specify the most canonical URLs for the original in cases where the data set or description is a simple publication of materials published elsewhere. The value of the sameAs needs to be unambiguously defined by the dataset - in other words, two different data sets should not use the same URL as the sameAs. Use the isBasedOn property when the reissued dataset (including metadata) has been significantly altered. When a dataset occurs or aggregates multiple originals, use the isBasedOn property. Use the ID property to attach any relevant digital object identifiers (DOIs) or compact identifiers. If the dataset has multiple identifiers, repeat the ID property. When using JSON-LD, this is presented using the syntax of the JSON list. We hope to improve our recommendations based on feedback, particularly around the description of origin, version and dates associated with the publication of the time series.