{"id":33820,"date":"2021-04-23T13:00:44","date_gmt":"2021-04-23T07:00:44","guid":{"rendered":"https:\/\/www.enago.com\/academy\/?p=33820"},"modified":"2023-01-06T18:01:28","modified_gmt":"2023-01-06T12:01:28","slug":"guest-post-navigate-sharing-your-research-data-with-dataseer","status":"publish","type":"post","link":"https:\/\/www.enago.com\/academy\/guest-post-navigate-sharing-your-research-data-with-dataseer\/","title":{"rendered":"Navigate Sharing Your Research Data With DataSeer"},"content":{"rendered":"<p><i>This guest post is drafted by an expert team from DataSeer. It is an intuitive interface that assists in streamlining the process of sharing and preservation of research data.<\/i><\/p>\n<p>Science advances on the incremental discoveries of thousands of people working through difficult problems. This advancement is, unfortunately, hampered by a lack of accessible data underlying these research discoveries. Freely accessible data would have the benefit of speeding the rate of discoveries. Furthermore, it would allow for a more thorough understanding of progress than is possible by one group working alone.<br \/>\nIn addition, open research data are crucial for public<a href=\"https:\/\/www.pewresearch.org\/science\/2019\/08\/02\/trust-and-mistrust-in-americans-views-of-scientific-experts\/\" target=\"_blank\" rel=\"noopener nofollow\"> building trust in research<\/a> \u2013 an important consideration in these days of scientific skepticism and misinformation. One of the pillars of the <a href=\"https:\/\/www.enago.com\/academy\/how-open-science-is-helping-researchers-succeed\/\" target=\"_blank\" rel=\"noopener\">Open Science movement<\/a> is making data sharing of research articles much more widespread. In fact, many journals and funders have already implemented mandatory data sharing policies. One of the largest challenges with Open Research Data is linking these data sharing requirements to the actions needed by authors to share data for their particular articles.<br \/>\n<img decoding=\"async\" class=\"aligncenter size-full wp-image-33837 lazyload\" data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer1.png\" alt=\"\" width=\"1286\" height=\"691\" data-srcset=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer1.png 1286w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer1-428x230.png 428w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer1-750x403.png 750w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer1-768x413.png 768w\" data-sizes=\"(max-width: 1286px) 100vw, 1286px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1286px; --smush-placeholder-aspect-ratio: 1286\/691;\" \/><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_74 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.enago.com\/academy\/guest-post-navigate-sharing-your-research-data-with-dataseer\/#The_Revolutionary_DataSeer_Approach\" >The Revolutionary DataSeer Approach<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.enago.com\/academy\/guest-post-navigate-sharing-your-research-data-with-dataseer\/#How_Does_DataSeer_Achieve_All_This\" >How Does DataSeer Achieve All This?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.enago.com\/academy\/guest-post-navigate-sharing-your-research-data-with-dataseer\/#Who_Does_DataSeer_Help\" >Who Does DataSeer Help?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.enago.com\/academy\/guest-post-navigate-sharing-your-research-data-with-dataseer\/#The_Future_of_Open_Data_is_Approaching\" >The Future of Open Data is Approaching<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"The_Revolutionary_DataSeer_Approach\"><\/span>The Revolutionary DataSeer Approach<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><strong>DataSeer<\/strong> is an AI app that guides users through the what, how, when, and where of sharing research data. Identifying the data sets in one&#8217;s own article seems trivial at first glance! However, it can quickly become complicated when questions of whether sharing raw data is enough, or if the downstream processed data are required instead, or both? This difficulty is greatly magnified if the person assessing data sharing compliance is a journal editor rather than the author. This happens as journal editors lack the authors\u2019 first-hand understanding of what went into the article.<br \/>\n<img decoding=\"async\" class=\"aligncenter size-full wp-image-33843 lazyload\" data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer5.png\" alt=\"\" width=\"320\" height=\"92\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 320px; --smush-placeholder-aspect-ratio: 320\/92;\" \/>Using Natural Language Processing and textual cues, <strong>DataSeer<\/strong> collects and separates sentences that describe data collection. Look below for an example. Furthermore, it infers the type of data being collected, and then identifies the data sets that need to be shared. <strong>DataSeer<\/strong> shows authors which data sharing repositories are most appropriate given their circumstances. These may include the type of data, the type of organism they\u2019re working with, and any repository preferences expressed by their journal, institution, or funding agency.<br \/>\n<img decoding=\"async\" class=\"aligncenter size-full wp-image-33839 lazyload\" data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer2.png\" alt=\"\" width=\"765\" height=\"169\" data-srcset=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer2.png 765w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer2-470x104.png 470w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer2-750x166.png 750w\" data-sizes=\"(max-width: 765px) 100vw, 765px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 765px; --smush-placeholder-aspect-ratio: 765\/169;\" \/>Once authors have been guided through sharing their data on public repositories, DataSeer creates an open certificate. The authors can use this certificate to demonstrate gold-standard compliance with open data policies to other stakeholders, such as their institution or funder. This certification process also generates a permanent, public link between that manuscript and the associated datasets. This step greatly improves the discoverability of both and allowing others to easily track dataset generation and reuse.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_Does_DataSeer_Achieve_All_This\"><\/span>How Does DataSeer Achieve All This?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><a href=\"https:\/\/dataseer.ai\/\" target=\"_blank\" rel=\"nofollow noopener\">DataSeer<\/a> has three main parts &#8211; the algorithm, the user interface, and the \u2018<a href=\"https:\/\/wiki.dataseer.ai\/doku.php?id=data_type\" target=\"_blank\" rel=\"nofollow noopener\">Research Data Wiki<\/a>\u2019. The <strong>DataSeer<\/strong> team has trained the algorithm on over 50,000 sentences from open access articles from journals like PLOS ONE and Scientific Reports. This rigorous approach enables it to handle research articles from a wide range of subject areas. The user interface allows researchers or journals to upload text from articles, and provides a report of the datasets in the article and how to share them. The Wiki hosts best-practice advice for sharing many different types of data. The goal is that widespread use of <strong>DataSeer<\/strong> will eventually lead to a global resource on best-practice for data sharing across all areas of research.<br \/>\n<img decoding=\"async\" class=\"aligncenter size-full wp-image-33840 lazyload\" data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer3.png\" alt=\"\" width=\"840\" height=\"455\" data-srcset=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer3.png 840w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer3-425x230.png 425w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer3-750x406.png 750w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer3-768x416.png 768w\" data-sizes=\"(max-width: 840px) 100vw, 840px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 840px; --smush-placeholder-aspect-ratio: 840\/455;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Who_Does_DataSeer_Help\"><\/span>Who Does DataSeer Help?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>In this age of misinformation and instant sharing, it is key to establish trust in sources and publications. <strong>DataSeer<\/strong> provides the pathway for efficiently increasing the proportion of articles that are accompanied by open data. In addition, it aids in increasing the quality and completeness of those open datasets.<\/p>\n<h3>Authors and Researchers<\/h3>\n<p>DataSeer\u2019s innovation is to use the efficiency of machine learning and natural language processing to automate a really difficult step in enforcing data sharing policies. This includes working out what the authors of a particular article need to do, and helping them do it. At some journals this step is performed by PhD level data curation experts. However, as each article can take them between 30 minutes and an hour to process, this approach is only practical for accepted manuscripts at well-resourced publishers. By making this process much cheaper and quicker, DataSeer will enable many more journals to adopt data sharing policies.<\/p>\n<p>Moreover, because <strong>DataSeer<\/strong> is inexpensive and highly scalable, it enables journals to require that all submitted articles share their data, so that the datasets can be scrutinized during <a href=\"https:\/\/www.enago.com\/publication-support-services\/peer-review-process\" data-internallinksmanager029f6b8e52c=\"115\" title=\"Peer Review\" target=\"_blank\" rel=\"noopener\">peer review<\/a>. This in turn will prompt researchers to be more rigorous with their data management throughout the research cycle. Furthermore, it should ultimately improve the overall reliability of published work.<\/p>\n<p><strong>DataSeer<\/strong> will also ensure that a much higher proportion of articles share their data, and also do a better job of sharing all of their datasets. Many more datasets will be available for testing new hypotheses, conducting powerful meta-analysis, or just verifying the authors\u2019 results. This is the crux of DataSeer\u2019s innovation: by fixing an apparently minor stumbling block in the peer review process, a revolution in open science is ushered in.<br \/>\n<img decoding=\"async\" class=\"aligncenter size-full wp-image-33841 lazyload\" data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer4.png\" alt=\"\" width=\"813\" height=\"117\" data-srcset=\"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer4.png 813w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer4-470x68.png 470w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer4-750x108.png 750w, https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/DataSeer4-768x111.png 768w\" data-sizes=\"(max-width: 813px) 100vw, 813px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 813px; --smush-placeholder-aspect-ratio: 813\/117;\" \/><\/p>\n<h3>Journals, Publishers, Institutions, &amp; Funding Agencies<\/h3>\n<p>Most stakeholders recognize the urgent need to improve the amount and quality of shared research data. Despite their efforts, compliance with data sharing policies (no matter how strongly worded) is frustratingly low. Additionally, the efforts to educate researchers about data sharing and open science are piecemeal and poorly attended. Human curators can ensure that authors of research articles share all of their data. However, since each article requires 15-45 minutes of effort this approach is only available to well-resourced journals. The high-touch human approach is clearly very hard to scale across the c. <a href=\"https:\/\/www.stm-assoc.org\/2015_02_20_STM_Report_2015.pdf\" target=\"_blank\" rel=\"nofollow noopener\" class=\"broken_link\">2.5 million research articles<\/a> published each year.<\/p>\n<p><strong>DataSeer\u2019s<\/strong> uses AI and Natural Language Processing to massively scale the <a href=\"https:\/\/www.fasebj.org\/doi\/full\/10.1096\/fj.12-218164\" target=\"_blank\" rel=\"nofollow noopener\" class=\"broken_link\">demonstrably successful <\/a>human curation approach. We define the data sharing actions the authors need to take <em>right now<\/em> for <em>this particular article<\/em>, lead them through the process, and report on their efforts to the relevant stakeholder. We are collaborating with DataCite to better guide researchers towards the most suitable data repositories. In addition, it will also help them in actively filtering <strong>DataSeer&#8217;s<\/strong> recommendations according to the journal, author institution, and funding agency associated with a particular article.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Future_of_Open_Data_is_Approaching\"><\/span>The Future of Open Data is Approaching<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><strong>DataSeer<\/strong> will highlight exactly what needs to be done with authors\u2019 data. By doing so, it will drive a system change in how journals promote Open Research Data. This shall greatly increase both the proportion of articles with open data and the completeness of the datasets shared alongside each article!<\/p>\n<div style=\"display:flex; gap:10px;justify-content:\" class=\"wps-pgfw-pdf-generate-icon__wrapper-frontend\">\n\t\t<a  href=\"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/posts\/33820?action=genpdf&amp;id=33820\" class=\"pgfw-single-pdf-download-button\" ><img data-src=\"https:\/\/www.enago.com\/academy\/wp-content\/plugins\/pdf-generator-for-wp\/admin\/src\/images\/PDF_Tray.svg\" title=\"Generate PDF\" style=\"width:auto; height:45px;\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\"><\/a>\n\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>This guest post is drafted by an expert team from DataSeer. It is an intuitive&hellip;<\/p>\n","protected":false},"author":8169,"featured_media":33845,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"footnotes":""},"categories":[751,754],"tags":[1522,1614,1623],"ppma_author":[1908],"class_list":["post-33820","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publication-stages","category-publication-ethics","tag-digital-tools-for-researchers","tag-guest-post","tag-open-science"],"better_featured_image":{"id":33845,"alt_text":"","caption":"","description":"","media_type":"image","media_details":{"width":750,"height":430,"file":"2021\/04\/pexels-olya-kobruseva-5561923.jpg","sizes":{"medium":{"file":"pexels-olya-kobruseva-5561923-401x230.jpg","width":401,"height":230,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-401x230.jpg"},"thumbnail":{"file":"pexels-olya-kobruseva-5561923-170x150.jpg","width":170,"height":150,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-170x150.jpg"},"lksg_gallery_admin_thumb":{"file":"pexels-olya-kobruseva-5561923-300x300.jpg","width":300,"height":300,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-300x300.jpg"},"lksg_gallery_admin_medium":{"file":"pexels-olya-kobruseva-5561923-400x400.jpg","width":400,"height":400,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-400x400.jpg"},"lksg_gallery_admin_large":{"file":"pexels-olya-kobruseva-5561923-500x430.jpg","width":500,"height":430,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-500x430.jpg"},"lksg_gallery_admin_medium_auto":{"file":"pexels-olya-kobruseva-5561923-400x430.jpg","width":400,"height":430,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-400x430.jpg"},"lksg_gallery_admin_large_auto":{"file":"pexels-olya-kobruseva-5561923-500x430.jpg","width":500,"height":430,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-500x430.jpg"},"tf-client-image-size":{"file":"pexels-olya-kobruseva-5561923-120x120.jpg","width":120,"height":120,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-120x120.jpg"},"publisher-tb1":{"file":"pexels-olya-kobruseva-5561923-86x64.jpg","width":86,"height":64,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-86x64.jpg"},"publisher-sm":{"file":"pexels-olya-kobruseva-5561923-210x136.jpg","width":210,"height":136,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-210x136.jpg"},"publisher-mg2":{"file":"pexels-olya-kobruseva-5561923-279x220.jpg","width":279,"height":220,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-279x220.jpg"},"publisher-md":{"file":"pexels-olya-kobruseva-5561923-357x210.jpg","width":357,"height":210,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-357x210.jpg"},"publisher-tall-sm":{"file":"pexels-olya-kobruseva-5561923-180x217.jpg","width":180,"height":217,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-180x217.jpg"},"publisher-tall-lg":{"file":"pexels-olya-kobruseva-5561923-267x322.jpg","width":267,"height":322,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-267x322.jpg"},"publisher-tall-big":{"file":"pexels-olya-kobruseva-5561923-368x430.jpg","width":368,"height":430,"mime-type":"image\/jpeg","source_url":"https:\/\/www.enago.com\/academy\/wp-content\/uploads\/2021\/04\/pexels-olya-kobruseva-5561923-368x430.jpg"},"Book 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It is also a popular platform for networking, allowing researchers to learn, share, and discuss their experiences within their network and community. The team, which comprises subject matter experts, academicians, trainers, and technical project managers, are passionate about helping researchers at all levels establish a successful career, both within and outside academia."}],"_links":{"self":[{"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/posts\/33820","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/users\/8169"}],"replies":[{"embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/comments?post=33820"}],"version-history":[{"count":0,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/posts\/33820\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/media\/33845"}],"wp:attachment":[{"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/media?parent=33820"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/categories?post=33820"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/tags?post=33820"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.enago.com\/academy\/wp-json\/wp\/v2\/ppma_author?post=33820"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}