{"id":{"repo_id":"texas-state","oai_identifier":"oai:digital.library.txst.edu:10877/9171"},"canonical_url":"https://search.dev.ndltd.org/etd/texas-state/oai:digital.library.txst.edu:10877/9171","repository":{"repo_id":"texas-state","name":"Texas State University","base_url":"https://digital.library.txst.edu/server/oai/request"},"display":{"title":"Methodology and Algorithm Development for Historical Addresses","abstract":"Historical GIS is a unique relationship between historical studies, geography, and geographic information science (GIS). This area of study combines several components of various fields and the use of new techniques and technologies to yield new questions, answers, and perspectives on datasets. In this paper, a generalized methodology is created and discussed to process a large historical data set. The dataset consisted of a record of Jewish people who were placed in Budapest which was created shortly after the end of World War II. Several pieces of information were found within the dataset, which included personal information along with addresses for where they lived. The addresses were normalized and joined to another dataset that was manually created for the same area and time from a different dataset. The whole dataset was also geocoded and processed to snap to a streets layer. A program was developed to fully encompass the methodology and would allow the use of any of the created functions to be used at any time.","abstract_html":"Historical GIS is a unique relationship between historical studies, geography, and geographic information science (GIS). This area of study combines several components of various fields and the use of new techniques and technologies to yield new questions, answers, and perspectives on datasets. In this paper, a generalized methodology is created and discussed to process a large historical data set. The dataset consisted of a record of Jewish people who were placed in Budapest which was created shortly after the end of World War II. Several pieces of information were found within the dataset, which included personal information along with addresses for where they lived. The addresses were normalized and joined to another dataset that was manually created for the same area and time from a different dataset. The whole dataset was also geocoded and processed to snap to a streets layer. A program was developed to fully encompass the methodology and would allow the use of any of the created functions to be used at any time.","abstract_has_math":false,"creators":["McNew, Keagan"],"institution":"Texas State University","degree_name":"Masters of Applied Geography","degree_level":"Masters","degree_discipline":"Geographic Information Science","degree_department":null,"school":null,"contributors":[],"advisors":["Giordano, Alberto"],"committee_chairs":[],"committee_members":["Cole, Tim"],"year":2019,"date_issued":"2019-08","date_published":"2019-08","updated_at":"2026-07-27T21:22:47Z","subjects":["historical GIS","geographic information science","python","geocoding","algorithms"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10877/9171","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Giordano, Alberto"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Cole, Tim"]},{"key":"dc:creator","label":"Author","values":["McNew, Keagan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-01-13T18:01:36Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-01-13T18:01:36Z"]},{"key":"dc:date.issued","label":"Date","values":["2019-08"]},{"key":"dc:type","label":"Dc Type","values":["Research Project"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geographic Information Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Masters of Applied Geography"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Texas State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["historical GIS","geographic information science","python","geocoding","algorithms"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10877/9171"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Applied Geography Directed Research"]},{"key":"dc:description.abstract","label":"Abstract","values":["Historical GIS is a unique relationship between historical studies, geography, and geographic information science (GIS). 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This area of study combines several components of various fields and the use of new techniques and technologies to yield new questions, answers, and perspectives on datasets. In this paper, a generalized methodology is created and discussed to process a large historical data set. The dataset consisted of a record of Jewish people who were placed in Budapest which was created shortly after the end of World War II. Several pieces of information were found within the dataset, which included personal information along with addresses for where they lived. The addresses were normalized and joined to another dataset that was manually created for the same area and time from a different dataset. The whole dataset was also geocoded and processed to snap to a streets layer. 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