{"id":18490,"date":"2021-03-31T10:42:59","date_gmt":"2021-03-31T10:42:59","guid":{"rendered":"https:\/\/www.rmsi.com\/blog\/?p=18490"},"modified":"2021-04-01T13:13:23","modified_gmt":"2021-04-01T13:13:23","slug":"enhancing-indias-health-facility-database-in-openstreetmap","status":"publish","type":"post","link":"https:\/\/www.rmsi.com\/blog\/2021\/03\/enhancing-indias-health-facility-database-in-openstreetmap\/","title":{"rendered":"Enhancing India\u2019s Health Facility Database in OpenStreetMap"},"content":{"rendered":"<p>In India almost 66% population lives in rural areas. The vital health services in these areas are provided by hospitals with emergency services and other small healthcare centers often serving as the foundations of rural health care delivery systems. Public healthcare is free for every Indian resident.\u00a0But, long travel distance is one of the\u00a0key challenges that rural citizens\u00a0encounter\u00a0to access and seek health care services in these nearby hospitals, as\u00a0they normally serve multiple communities within a large region.<\/p>\n<p><em>When a natural disaster, accidents, other emergency cases or disease outbreak occurs there is a rush to establish accurate health care location data that can be used to support response and recovery teams on ground.<\/em> Access to healthcare is a requirement for human well-being that is constrained, in part, by the allocation of healthcare resources relative to the geographically dispersed human population.<\/p>\n<div id=\"wpc_6065be40ec426\" class=\"vc_row wpb_row vc_row-fluid \">\n<div class=\"row_inner_wrapper clearfix\">\n<div class=\"row_inner row_center_content clearfix\">\n<div class=\"wpb_column vc_column_container vc_col-sm-12\">\n<div class=\"vc_column-inner \">\n<div class=\"wpb_wrapper\">\n<p class=\"vc_custom_heading\">At RMSI, we\u00a0are committed to addressing global issues of human habitation, security &amp; safety connected with food, calamities, use of natural resources.\u00a0While assessing solutions to the above healthcare challenges,\u00a0our mapping experts noticed that a lot of hospitals or healthcare centers didn\u2019t even exist on most of the maps.<\/p>\n<p class=\"vc_custom_heading\"><em>We believe strongly that the solution to most problems starts with getting the right data.\u00a0<\/em><\/p>\n<p><strong>Map Intelligence with OpenStreetMap (OSM):<\/strong><\/p>\n<p class=\"vc_custom_heading\">There are various online mapping platforms that provides mapping services across the globe, and one such popular open-source platform is OSM, a free and openly editable map of the world. OSM is a web-based public platform that collects data describing the position of roads, rivers, towns, point of interests, etc. used to create maps.<\/p>\n<p class=\"vc_custom_heading\"><strong>RMSI recently\u00a0worked on enhancing the healthcare facility database in the country.\u00a0The overall objective is to improve the Health facility POI in OSM data across the country (India) with the help of Government approved database and latest available imagery.<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<figure id=\"attachment_18523\" aria-describedby=\"caption-attachment-18523\" style=\"width: 600px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-18523\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_01-2.jpg\" alt=\"\" width=\"600\" height=\"276\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_01-2.jpg 855w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_01-2-300x138.jpg 300w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_01-2-768x353.jpg 768w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><figcaption id=\"caption-attachment-18523\" class=\"wp-caption-text\">Detailed Progress of India&#8217;s Health Facilities Import<\/figcaption><\/figure>\n<p><strong>1. Data Resources<\/strong><\/p>\n<p>Our experts\u00a0referred to the\u00a0following open sources of data.<\/p>\n<p>The OGD (Open Government Data) data was taken\u00a0by the Government of the country or any government-controlled entities. <a href=\"https:\/\/data.gov.in\">https:\/\/data.gov.in<\/a> \u00a0is a platform\u00a0that is supporting open data initiative of the Government of India.<\/p>\n<p>\u201cOpen Data\u201d platform is being offered to other countries and implemented in US as their <a href=\"http:\/\/data.gov\/\">data.gov<\/a>. Few other countries are also being powered by Open data platform. Example: Ghana.<\/p>\n<ul>\n<li><strong>OGD (Open Gov Data)<\/strong> &#8211; Hospital Directory<\/li>\n<li><strong>OGD<\/strong> <strong>(Open Gov Data)<\/strong> &#8211; NIN Health facilities Directory<\/li>\n<li><strong>OGD (Open Gov Data) &#8211;<\/strong> Blood banks Directory<\/li>\n<\/ul>\n<p><strong>2. OpenStreetMap &#8211; India Health Facilities Import Process<\/strong><\/p>\n<p><strong>2.1 Process &amp; Workflow\u00a0<\/strong><\/p>\n<p>All the government datasets&#8217; records are\u00a0filtered and double-checked before importing in the OpenStreetMap. OSM Import guidelines have been\u00a0followed while\u00a0initiating the Health Facilities Import Process.<\/p>\n<p><a href=\"https:\/\/wiki.openstreetmap.org\/wiki\/India_Health_Facilities_Import\">https:\/\/wiki.openstreetmap.org\/wiki\/India_Health_Facilities_Import<\/a><\/p>\n<figure id=\"attachment_18495\" aria-describedby=\"caption-attachment-18495\" style=\"width: 507px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-18495\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_02.jpg\" alt=\"\" width=\"507\" height=\"338\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_02.jpg 507w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_02-300x200.jpg 300w\" sizes=\"auto, (max-width: 507px) 100vw, 507px\" \/><figcaption id=\"caption-attachment-18495\" class=\"wp-caption-text\">Flowchart for Health Facilities Import<\/figcaption><\/figure>\n<p><strong>2.2 Data Preparation<\/strong><\/p>\n<p>In the first phase of the import process, RMSI team split each directories into small datasets based on States and cities of India.<\/p>\n<figure id=\"attachment_18496\" aria-describedby=\"caption-attachment-18496\" style=\"width: 510px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18496\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_03.jpg\" alt=\"\" width=\"510\" height=\"214\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_03.jpg 667w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_03-300x126.jpg 300w\" sizes=\"auto, (max-width: 510px) 100vw, 510px\" \/><figcaption id=\"caption-attachment-18496\" class=\"wp-caption-text\">Splitting of Directories in to Small Datasets based on Cities &amp; States<\/figcaption><\/figure>\n<p>The input data had few quality issues that were\u00a0addressed immediately and further cleaned on the basis of values before the import. All the record of government datasets were ensured to\u00a0be verified before importing into OSM.<\/p>\n<p>The input data sets were further\u00a0sanitized on the basis of<\/p>\n<ol>\n<li>Removal of invalid values &#8211; N\/A, 0, \/N, Blanks,\u00a0etc.<\/li>\n<li>Cleaning of duplicates<\/li>\n<li>Proper transcription<\/li>\n<li>Convert the OGD attributes to OSM compatibility tag.<\/li>\n<\/ol>\n<ul>\n<li>JOSM validations were performed for cleanup of files and converted into geoJSON files before importing to OSM.<\/li>\n<\/ul>\n<figure id=\"attachment_18497\" aria-describedby=\"caption-attachment-18497\" style=\"width: 433px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-18497\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_04.jpg\" alt=\"\" width=\"433\" height=\"240\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_04.jpg 433w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_04-300x166.jpg 300w\" sizes=\"auto, (max-width: 433px) 100vw, 433px\" \/><figcaption id=\"caption-attachment-18497\" class=\"wp-caption-text\">Viewing the Validation and Conversion of Files<\/figcaption><\/figure>\n<p><strong>2.3 Data Execution<\/strong><\/p>\n<p>Every\u00a0State Government&#8217;s hospital data was\u00a0then revalidated and compared with the existing OSM data. The data import was performed\u00a0using the import specific accounts and also by specific change set comments.<\/p>\n<figure id=\"attachment_18498\" aria-describedby=\"caption-attachment-18498\" style=\"width: 522px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18498\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_05.jpg\" alt=\"\" width=\"522\" height=\"195\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_05.jpg 575w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_05-300x112.jpg 300w\" sizes=\"auto, (max-width: 522px) 100vw, 522px\" \/><figcaption id=\"caption-attachment-18498\" class=\"wp-caption-text\">Importing Data in OSM<\/figcaption><\/figure>\n<p><strong>2.4 Quality Assurance<\/strong><\/p>\n<p>Conflation Tools were used to check for duplicates with the existing data and OGD data sets. Quality checks were performed using the JOSM tools before and after every import and was repeated for all the sub-datasets.<\/p>\n<figure id=\"attachment_18499\" aria-describedby=\"caption-attachment-18499\" style=\"width: 528px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-18499\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_06.jpg\" alt=\"\" width=\"528\" height=\"288\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_06.jpg 528w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_06-300x164.jpg 300w\" sizes=\"auto, (max-width: 528px) 100vw, 528px\" \/><figcaption id=\"caption-attachment-18499\" class=\"wp-caption-text\">Quality Checks Performed using JOSM Tool<\/figcaption><\/figure>\n<p><strong>2.5 Smart Practices for Data Import<\/strong><\/p>\n<p>RMSI used Government approved websites to check for the available information\u00a0on Health Facilities to ensure the completeness and quality of the data. A written checklist was followed by\u00a0the team to ensure the quality and specifications were\u00a0in met\u00a0during production and review stage before the final delivery.<\/p>\n<h3><strong>3. Health Facility POIs before Import &amp; Current Data<\/strong><\/h3>\n<figure id=\"attachment_18500\" aria-describedby=\"caption-attachment-18500\" style=\"width: 523px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18500\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_07.jpg\" alt=\"\" width=\"523\" height=\"239\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_07.jpg 764w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_07-300x137.jpg 300w\" sizes=\"auto, (max-width: 523px) 100vw, 523px\" \/><figcaption id=\"caption-attachment-18500\" class=\"wp-caption-text\">Detailed Picture Showing Before and After Health Facilities Import<\/figcaption><\/figure>\n<h3><strong>4. Few Enhancements in Data<\/strong><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-18527 alignnone\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_021.jpg\" alt=\"\" width=\"600\" height=\"370\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_021.jpg 600w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_021-300x185.jpg 300w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/p>\n<p>With the help of input data records (OGD), RMSI team added more valuable attributes to existing OSM data.<\/p>\n<p><strong>Example 1<\/strong>: Missing hospitals were\u00a0identified and hospital\/ building features were added in OSM data<\/p>\n<p><strong>Example 2<\/strong>: Existing hospital data was modified by adding all the proper tags and complete addresses to the health facility POI<\/p>\n<p><strong>Example 3<\/strong>: Duplicate entries were removed from existing data and corrected by cleaning up of duplications<\/p>\n<p><strong>Example 4<\/strong>: Building feature geometry was improved for existing data and tag correction was made as per OSM tagging guidelines.<\/p>\n<h3><strong>5. Field Survey for Telangana State<\/strong><\/h3>\n<p>RMSI team first designed and developed an in-house application with customized functionality to fit our survey method. We then sorted all unsuccessful records district-wise and distributed them to each squad to collect locations of the remaining OGD data in Telangana. With the help of our application, our team captured the locations of the missing facility more efficiently and in a timely manner.<\/p>\n<figure id=\"attachment_18507\" aria-describedby=\"caption-attachment-18507\" style=\"width: 498px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18507\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_014.jpg\" alt=\"\" width=\"498\" height=\"238\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_014.jpg 582w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_014-300x143.jpg 300w\" sizes=\"auto, (max-width: 498px) 100vw, 498px\" \/><figcaption id=\"caption-attachment-18507\" class=\"wp-caption-text\">Field Survey Application &amp; Team Field Surveying<\/figcaption><\/figure>\n<figure id=\"attachment_18508\" aria-describedby=\"caption-attachment-18508\" style=\"width: 489px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18508\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_015.jpg\" alt=\"\" width=\"489\" height=\"208\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_015.jpg 668w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_015-300x128.jpg 300w\" sizes=\"auto, (max-width: 489px) 100vw, 489px\" \/><figcaption id=\"caption-attachment-18508\" class=\"wp-caption-text\">Field Survey Planning for Telangana State<\/figcaption><\/figure>\n<h3><strong>6. Map Roulette Challenges<\/strong><\/h3>\n<p>With full support on the import from the OSM community, RMSI team\u00a0initiated the\u00a0import\u00a0of the local regions, by creating Map Roulette challenges to verify the position of each data point from the cleaned and verified datasets.<\/p>\n<figure id=\"attachment_18509\" aria-describedby=\"caption-attachment-18509\" style=\"width: 489px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18509\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_016.jpg\" alt=\"\" width=\"489\" height=\"222\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_016.jpg 559w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_016-300x136.jpg 300w\" sizes=\"auto, (max-width: 489px) 100vw, 489px\" \/><figcaption id=\"caption-attachment-18509\" class=\"wp-caption-text\">Map Roulette Challenges<\/figcaption><\/figure>\n<p>RMSI\u00a0also organized an OSM (OpenStreetMap) awareness program in December 2019, at Jawaharlal Nehru Government Polytechnic College in Ramanthapur, Hyderabad.<\/p>\n<p><b>The goal of the workshop was to increase awareness about OpenStreetMap, its uses in times of a disaster or crisis management. It focused\u00a0on how to reduce the disaster risk and enable a speedy recovery through these maps<\/b>.<strong>\u00a0<\/strong><\/p>\n<p>To spread awareness about OSM among college students, various GIS (Geography Information System) related activities were conducted to map the areas and places around the world. The workshop was held in two modules: OSM awareness training and OSM practical training,\u00a0as highlighted in our previous blog <a href=\"https:\/\/www.rmsi.com\/blog\/2020\/01\/spreading-awareness-about-mapping-on-osm-a-free-and-openly-editable-map-of-the-world\/\">Spreading Awareness About Mapping on OSM, a Free and Openly Editable Map of the World (rmsi.com)<\/a>.<\/p>\n<figure id=\"attachment_18510\" aria-describedby=\"caption-attachment-18510\" style=\"width: 489px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18510\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_017.jpg\" alt=\"\" width=\"489\" height=\"225\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_017.jpg 576w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_017-300x138.jpg 300w\" sizes=\"auto, (max-width: 489px) 100vw, 489px\" \/><figcaption id=\"caption-attachment-18510\" class=\"wp-caption-text\">OSM Awareness Program by RMSI<\/figcaption><\/figure>\n<h3><strong>7. Survey Utilities<\/strong><\/h3>\n<p>RMSI has developed an application to perform field survey for Telangana State.<\/p>\n<figure id=\"attachment_18511\" aria-describedby=\"caption-attachment-18511\" style=\"width: 485px\" class=\"wp-caption alignnone\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-18511\" src=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_018.jpg\" alt=\"\" width=\"485\" height=\"261\" srcset=\"https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_018.jpg 531w, https:\/\/www.rmsi.com\/blog\/wp-content\/uploads\/2021\/03\/blg_mar21_018-300x162.jpg 300w\" sizes=\"auto, (max-width: 485px) 100vw, 485px\" \/><figcaption id=\"caption-attachment-18511\" class=\"wp-caption-text\">Application Used for Telangana Field Survey<\/figcaption><\/figure>\n<h3><strong>8. Data Maintenance<\/strong><\/h3>\n<p>As OSM is an open-source platform, there are always constant modifications required in data and frequent updates are required in real time. Hence, maintenance plays a prominent role for safeguarding the data.\u00a0We use ArcGIS tool to constantly monitor the data and address all the new additions and deletion of existing health facilities. Maintenance team, simultaneously, validates the changes with all the available resources and make necessary changes.<\/p>\n<p><strong>Acknowledgments<\/strong><strong>\u00a0<\/strong><\/p>\n<p><a href=\"https:\/\/wiki.openstreetmap.org\/wiki\/RMSI\">RMSI<\/a>\u00a0is currently working to support expanded Information Management capacity within India. The project aimed to provide accessible data of accurate health care information from the\u00a0<a href=\"https:\/\/data.gov.in\/\">Open Government Data<\/a>\u00a0directories for Hospitals, Health facilities, Blood banks, Health Centers and Health Clinics information which can be useful for all the people and also\u00a0for Humanitarian causes. Core to the above goal, is also ensuring that this dataset of health facility data is easily accessible to everyone.<\/p>\n<p>If you are interested in our progress, please keep watching the periodical updates on our import wiki. If you are interested in improving the health facilities in your local region please contact us at\u00a0<a href=\"mailto:osm@rmsi.com\">osm@rmsi.com<\/a>\u00a0so that\u00a0we can share\u00a0maproulette for your region.<\/p>\n<p><strong>Happy Mapping!<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In India almost 66% population lives in rural areas. The vital health services in these areas are provided by hospitals with emergency services and other small healthcare centers often serving as the foundations of rural health care delivery systems. Public healthcare is free for every Indian resident.\u00a0But, long travel distance [&hellip;]<\/p>\n","protected":false},"author":32601,"featured_media":18516,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-18490","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-management"],"post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/posts\/18490","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/users\/32601"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/comments?post=18490"}],"version-history":[{"count":33,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/posts\/18490\/revisions"}],"predecessor-version":[{"id":18550,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/posts\/18490\/revisions\/18550"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/media\/18516"}],"wp:attachment":[{"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/media?parent=18490"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/categories?post=18490"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rmsi.com\/blog\/wp-json\/wp\/v2\/tags?post=18490"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}