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. Please join the discussion in the community. Text properties recommendations We recommend limiting all text properties to properties characters or less. Google Dataset Search uses only the first 5,000 characters of any text property. Names are usually a few words or a short sentence. Known bugs and warnings you may encounter errors or warnings in structured Google data testing tools and other verification systems. In particular, verification systems may assume that organizations should have contact information, including contactType; useful values include customer service, emergency, journalist, editorial and public engagement. You can also ignore errors for csvw:The table is an unexpected value for the core of the Society property. Structured definitions of the type of data you need to include the necessary properties for your content to be eligible to display as a rich result. You can also include recommended properties to add more information about your content that can provide a better user experience. You can use a structured data testing tool to check the markup. The focus is on describing information about the data set (its metadata) and presenting its contents. For example, the metadata of the dataset shows what is in the dataset, what variables it measures, who created it, and so on. For example, it does not contain specific values for variables. The Full DataSet is available by schema.org/Dataset. You can describe additional information about the publication of a data set, such as the license when it was published, its DOI, or sameAs, by pointing to the canonical version of the dataset in another repository. Add an ID, a license, and the same for datasets that provide origin and license information. The required property description is a Text Summary describing the data set. The guidelines of the Summary should be 50 to 5,000 characters in length. The summary may include Markdown syntax. Embedded images should use the URLs of the absolute path (instead of relative paths). When using the JSON-LD format, designate new lines (two characters: backshash and bottom letter n). Name Text The descriptive name of the data set. For example, the depth of snow in the Northern Hemisphere. The guidelines use unique names for different datasets whenever possible. Recommended: Snow depth in the Northern Hemisphere and depth of snow in the southern hemisphere for two different data sets. Not recommended: Snow depth and snow depth for two different data sets. Recommended properties alternate text Alternative names that were used to refer to this dataset, such as aliases or abbreviations. Example (in JSON-LD format): Name: Fast, draw! Alternative dataset: A quick data set dataset - The creator of Person or Organization Creator or author of this data set. To identify individuals uniquely, use ORCID ID as the value of the same Person property. Use ROR ID to identify institutions and organizations in a clear way. Example (in JSON-LD JSON-LD Creator: @type: Man, sameAs: givenName: Jane, FamilyName: Fu, Name: Jane Fu , @type: Person, sameAs: givenName: Jo @type: Organization, sameAs: Name: Fictitious Research Consortium - Quote Text or CreativeWork Identifies Academic Articles That Are Recommended by the Data Provider Cite the dataset itself with other properties such as name, ID, creator and publisher properties. For example, this property can unambiguously identify a related academic publication, such as a data handle, a data document, or an article for which this dataset is additional material. Examples (in JSON-LD format): quote: quote: 11111111 quote: 0111.1111v1 quote: Doe J (2014) Influence X ... Additional Recommendations Don't use this property to provide citation information for the data set itself. It is designed to identify related academic articles, not the data set itself. To provide the information you need to link to the dataset itself, use the properties of the name, ID, creator, and publisher instead. If you fill a citation property with a quote fragment, provide an article ID (such as a DOI) if possible. Recommended: Doe J (2014) Influence X. Biomics 1 (1). Not recommended: Doe J (2014) Influence X. Biomics 1 (1) has a Between or isPartOf URL or DataSet If the dataset is a set of smaller data sets, use hasPart to refer to such relationships. You can on the other hand, if the dataset is part of a larger data set, the use isPartOf. Both properties can take the form of a URL or a Dataset instance. If the dataset is used as a value, it should include all the properties needed for a standalone data set. Examples: hasPart: @type: Dataset, name: Subset of Data 01, Description: Information description of the first subset of data..., License: - @type: Dataset, name: Sub dataset 02, description: Information description of the second subset..., license: - isPartOf: URL ID, text or ID. If the dataset has multiple identifiers, repeat the ID property. When using JSON-LD, this is presented using the syntax of the JSON list. Keywords Text Keywords that summarize the data set. License URL or CreativeWork A, which distributes the data set. For example: For example: : license: @type: CreativeWork, name: Custom license, url: - Additional Guidelines Provide a URL that uniquely defines a specific version of the license used. Recommended License: Not recommended license: measurement Technician Text or URL Technique, technology or methodology used in a data set that may correspond to the variable (s) described in the variableMeasour. Measuring The property is also being offered while waiting for standardization at the schema.org. We encourage publishers to share any feedback about this property with schema.org community. The URL URL links a web page that clearly indicates the identity of the data set. spatialCoverage Text or Place You can provide a single point by describing the spatial aspect of the dataset. This property is only activated if the dataset has a spatial dimension. For example, one point where all the measurements were collected, or the coordinates of the box area. Spatial Broadcasting Points: - @type: Place, Geo: @type: GeoCoordinates, latitude: 39.3280, longitude: 120.1633 - Forms Use GeoShape to describe areas of different shapes. For example, specify a limit box. Spatial Announcement: - @type: Place, geo: @type: GeoShape, box: 39.3280 120.1633 40.445 123.7878 - Points inside the box, the properties of the circle, line or landfill should be expressed as a space separated by a couple of two values corresponding to latitude and long and (in this order). Named Location SpatialSource:Tahoe City, CA Temporary TextCoverage Data in the dataset covers a certain time interval. This property is only activated if the dataset has a time dimension. Schema.org uses ISO 8601 to describe time and time intervals. Dates can be described differently depending on the interval of the data set. Include open intervals with two decimal points (..). Single temporalCoverage Date: 2008 Temporary Period: 1950-01- 01/2013-12-18 Open Time Period Temporary Binding: 2013-12-19/. variableMeasured Text or PropertyValue variable that this data set measures. For example, temperature or pressure. It is proposed and expects standardization at present for schema.org. We encourage publishers to share any feedback about this property with schema.org community. text or version number number for the data set. URL Location of a page describing the data set. DataCatalog Full DataCatalog is available schema.org/DataCatalog. Datasets are often published in repositories that contain many other datasets. and the same data set can be included in several such repositories. You can turn to directory to which this dataset belongs, referring directly to it. Recommended properties are includedIndataCatalog DataCatalog Catalog, to which the data set belongs. DataDownload Full DataDownload is available on schema.org/DataDownload. In addition to Dataset properties, add the following properties for datasets that provide download options. The distribution property describes how to get the dataset itself because the URL often points to a landing page describing a data set. The distribution property describes where to get the data and in what format. This property can have several meanings: for example, the CSV version has one URL and the Excel version is available on another. Necessary properties distribution.contentUrl URL Link for download. Recommended Distribution of DataDownload Properties Location Description for downloading a dataset and file format for download. distribution.encodingFormat Text or URL Distribution File format. Beta Tablar Data Kits: This approach is currently in beta and therefore may be changing. The tablicular dataset is organized mainly in terms of a grid of rows and columns. For pages that embed data tables, you can also create a more clear markup based on the basic approach described above. We currently understand the CSVW (CSV on the Internet), see W3C, which is provided in parallel to user-centric tablicular content on the HTML page. Here's an example showing a small table encoded in CSVW JSON-LD format. There are some known errors in the Rich results test. The American Humane Association2015 - csvw:name: NTEE Code, csvw:datatype: row, csvw:cells: csvw:value: D200, csvw:notes: Animal protection and welfare, csvw:primaryKey: 2016 csvw:value: D200, csvw:notes: Animal protection and well-being, csvw:primary: 2015 csvw:name: General functional expenses ($), csvw:data: cs csvw:cells: csvw:value: 13800212, csvw:primaryKey: 2016 - csvw:value: 13800212, csvw:primaryKey: 2015 You don't need to sign up for a search console to be involved in Google search results, but it can help you understand and improve how Google sees your site. We recommend checking your search console in the following cases: After deploying structured data for the first time after Google indexed your pages, look for problems using the appropriate Rich result status report. Ideally you should see an increase in valid pages, and no increase in errors or warnings. If you find problems in structured data: after the release of new templates or code updates, when making significant changes to the website, watch out for an increase in structured errors and data alerts. If you see an increase in the number of bugs, you may have rolled out a new pattern that doesn't work, or your site interacts with the existing template in a new and bad way. If you see a decrease in actual items (not consistent with an increase in the number of bugs), you may no longer be embedding structured data on your pages. Use the URL verification tool to find out what is causing the problem. When you analyze traffic periodically, analyze Google search traffic with a performance report. The data will show you how often your page is displayed as a rich result in your search, how often users click on it, and what is the average position you display in search results. You can also automatically pull these results from the search console API. Troubleshooting Is Important: Google does not guarantee that features that consume structured data will appear in search results. A list of common reasons why Google may not show your content in a rich result, see If you're having trouble implementing structured data, here are some resources that can help you. A specific data set does not appear in the Dataset search results error what caused the problem: Your site has no structured data on the page that describes the data sets or the page has not been scanned yet. made Fix the Problem Copy link to the page you expect to see in The Dataset search results, and its in the test results of the rich. If a Page message appears that is not eligible for rich results known by this test or not all markups are eligible for rich results, it means that No dataset markup on the page or is wrong. You can fix this by referring to the How to Add Structured Data section. If there is a markup on the page, it may not have been scanned yet. You can check the scan status with a search console. The company logo is missing or not appearing correctly by error of results What caused the problem: Your page may be missing schema.org markup for the organization's logos or your business is not created with Google. done Fix the problem google dataset search api. google dataset search wiki. google dataset search by the numbers. google dataset search schema.org. google dataset search engine url. google dataset search blog. google dataset search out of beta. google dataset search pdf

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