glam-datasets: 832

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rowid dataset_title publisher author dataset_issued dataset_modified dataset_description source info_url start_date end_date file_title download_url format file_description file_created file_modified file_size licence
832 Passengers in History History Trust of South Australia History Trust of South Australia 2016-06-28T00:52:30.371967 2021-09-08T23:20:52.626089 _Passengers in History_ brings together two wonderful resources: <br /><br /> A passengers data base developed by the SA Maritime Museum, A list of ships’ logs and diaries, titled Log of Logs. <br /><br /> The passengers data base was produced by staff and volunteers at the South Australian Maritime Museum over 20 years. It includes entries for 328,000 passengers and 20,000 voyages to South Australia between 1836 and 1961. <br /><br /> This data set is presented as a search index that can expose most open data formats. 1836-01-01 1961-01-01 Passengers in History Search Index API #Passengers in History API Documentation# The Passengers in History data endpoint has been provided using an Apache Solr index (see that uses a Drupal Solr 4.x schema (see See []( for more detail surrounding the query syntax. <br /> An example of a basic implementation can be viewed at <br /> Replace the type parameter with any of the types listed below to return associated images eg. <br /> The example code can be downloaded from <br /> The open_data index contains 7 different types of content: <br /> * voyage * passenger * vessel * master * port * source * organisation <br/> Additionally, the photo index (photo_index) can be used to retrieve photos (specify the index using the index_id query parameter). <br/> A voyage is centric to most other content types contains references to passengers, vessels and ports. A join query should be used to get information about related content (see for information surrounding the query syntax for joins). The is_nid field is the unique identifier. <br/> The number of rows per query is limited to 999 so the start and rows query parameters would need to be used to iterate over the entire result set. <br/> There are many response formats available (see Just add the parameter 'wt' to the query and select the response format eg. json or csv. The default is xml. ##Examples## A typical workflow might be: <br/> Get the voyage/s that arrived in 1836: <br/> [ AND is_field_voyage_year:1836]( AND is_field_voyage_year:1836) <br/><br/> Use a join to get the passengers for one of the voyages (use the voyage is_nid field) <br/> [{!join from=im_field_passengers to=is_nid}index_id:open_data AND is_nid:944632]({!join from=im_field_passengers%20to=is_nid}index_id:open_data AND is_nid:944632) <br/><br/> Use a join to find the origin and destination of a particular voyage: <br/> [{!join from=is_field_origin to=is_nid}index_id:open_data AND is_nid:944632]({!join from=is_field_origin to=is_nid}index_id:open_data AND is_nid:944632) <br/> [{!join from=is_field_destination to=is_nid}index_id:open_data AND is_nid:944632]({!join from=is_field_destination to=is_nid}index_id:open_data AND is_nid:944632) <br/><br/> Use a join to find the vessel for the voyage: <br/> [{!join from=is_field_vessel to=is_nid}index_id:open_data AND is_nid:944632]({!join from=is_field_vessel to=is_nid}index_id:open_data AND is_nid:944632) <br/><br/> Use a join to find photos of the vessel (using the vessel is_nid): <br/> [ AND im_file_usage_list:920026]( AND im_file_usage_list:920026) <br/><br/> Use a join to find out where a vessel was built (using the vessel is_nid): <br/> [{!join from=is_field_built_where to=is_nid}index_id:open_data AND is_nid:923958]({!join from=is_field_built_where to=is_nid}index_id:open_data AND is_nid:923958) <br/><br/> Use a join to find the built by organisation for a particular vessel: <br/> [{!join from=is_field_built_by to=is_nid}index_id:open_data AND is_nid:923958]({!join%20from=is_field_built_by%20to=is_nid}index_id:open_data%20AND%20is_nid:923958) <br/><br/> Get organisation details (using the organisation is_nid): <br/> [ AND ss_type:organisation AND is_nid:916199]( <br/><br/> Or find all vessels built by the organisation (using the organisation is_nid): <br/> [ AND is_field_built_by:916199]( <br/><br/> ##Other Useful Queries Find all photos that are attached to a passenger: <br/>{!join from=is_nid to=im_file_usage_list}ss_type:(passenger OR image) <br/><br/> Or find all passengers that have a photo attached (the reverse): <br/>{!join from=im_file_usage_list to=is_nid}ss_type:(passenger OR image) <br/><br/> All fields are searchable (see listing below). There are many search options using the Apache Solr query syntax. For instance to find all vessels that have the word ‘Adelaide’ in their tm_title field but not the word ‘port’: <br/> AND ss_type:vessel AND tm_title:(adelaide -port) <br/> In this case ss_type is specifically set to be ‘vessel’. The – represents negation of the term. There are many more options – refer to a good blog here []( <br/><br/> Facet search on the voyage destination for a date range between 1834 and 1836: <br/>{!join%20from=is_nid%20to=is_field_destination}index_id:open_data&fq=ds_field_depart_date:[1834-01-01T00:00:00Z%20TO%201836-12-31T12:59:59Z]&facet=on&facet.field=is_field_destination <br/> In this case use a port search by node to get the titles of the ports eg.(using the first facet): <br/> <br/> The answer is most likely to be Sydney! <br/><br/> ##Content Type Fields## ###Passenger <br/> * is_nid * ss_type * tm_field_occupation * tm_field_surname * tm_field_firstname * is_field_age * is_arrival_year <br/> ###Voyage <br/> * is_nid * ss_type * ds_field_depart_date * is_field_destination * tm_field_master * is_field_origin * is_field_vessel * is_field_voyage_year * tm_title <br/> ###Vessel <br/> * is_nid * ss_type * tm_title * tm_field_services * im_field_sources * is_field_year_end * is_field_year_start * is_field_built_by * is_field_built_where * is_field_built_year * tm_field_demise * tm_field_rig * tm_field_dimensions * tm_field_tonnage <br/> ###Source <br/> * is_nid * ss_type * tm_title * tm_field_location * tm_field_reference <br/> ###Port <br/> * is_nid * ss_type * tm_title <br/> ###Organisation <br/> * is_nid * ss_type * tm_title <br/> ###Photos <br/> * is_fid: Unique ID for a file * tm_field_citation: Includes copyright information * tm_field_file_image_title_text: Image title * tm_field_location: Location of the image * tm_field_source: Source of the image * is_file_usage_count: Number of times this file is used in * im_file_usage_list: List of content that uses this file * ss_url: Url to the file 2016-06-28T10:54:22.341773     Creative Commons Attribution