{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78631"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78631","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Temporal Data Exchange and Repair","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Golshanara, Ladan"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Chomicki, Jan","Computer Science and Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:57:08Z","date_published":"2018-10-26T02:57:08Z","updated_at":"2026-07-27T19:05:14Z","subjects":["computer science"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78631","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chomicki, Jan","Computer Science and Engineering"]},{"key":"dc:creator","label":"Author","values":["Golshanara, Ladan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:57:08Z","2018","2018-08-10 14:03:18"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["computer science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78631"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Temporal data isneeded by many organizations and individuals to support audit trails. With temporal data one can represent when a fact is true and for how long. The temporality offacts is also critical in diverse domains, from medical diagnosis toassessing the changing business conditions of companies to taxi and rental bicycle rides. To support temporal database applications suitable database features wererecently added to the SQL:2011 standard, and adopted by major database management systems such as DB2,Oracle, and Teradata.In today's digital world information about an entity can be found at different data sources at different times or in different versions of the same source. Despite the need for frameworks for temporal data curation tasks including temporal data cleaning, temporal data transformation, temporal data exchange and temporal data provenance, there are no principled frameworks in the literature. The goal of this research is to address the challenges that arise when one considers temporal data in the frameworks of data exchange and repair. The approach and the results can be used in other temporal data curation tasks as well. The frameworks are based on a formal two-tier view of temporal data consisting of the concrete view and the abstract view. There are two models to show a temporal database in the abstract view: snapshot model and timestamp model. In the snapshot model, temporal data is shown as an infinite sequence of snapshots. In the timestamp model each fact in the database is associated with every time point in which it is true. There may be infinitely many such points because the database may extend arbitrarily far into the future. In the concrete view each fact is associated with the time interval(s) in which it is true. The concrete view provides efficiency in storing and manipulating data. In the first part of this dissertation, we show how the framework of data exchange can be systematically extendedto temporal data. We first extend the chase procedure for the abstract view using the snapshot model to have a conceptual basis for the data exchange for temporal databases. Considering non-temporal source-to-target tuple generating dependencies and equality generating dependencies, the chase algorithm can be applied on each snapshot independently. Then we define a chase procedure (called c-chase) on concrete instances and show the result of c-chase on a concrete instance is semantically aligned with the result of chase on the corresponding abstract instance. In order to interpret intervals as constants while checking if a dependency or a query is satisfied by a concrete database, we will normalize the instance with respect to the dependency or the query. To obtain the semantic alignment, the nulls (which are introduced by data exchange and model incompleteness) in the concrete view are annotated with temporal information. Furthermore, we show that the result of the concrete chase provides a foundation for query answering. We define naive evaluation on the result of the c-chase and show it produces certain answers. The second part of the dissertation aims to investigate temporal repair checking with respect to temporal functional dependencies. Same as temporal data exchange framework, building on the relational notion of repair we have defined concrete repairs. We have also examined how a temporal repair checking algorithm can handle infinite abstract databases. We show how to reduce the problem of temporal repair checking on infinite temporal databases to the problem of temporal repair checking on finite temporal databases. We also develop two temporal repair construction algorithms: one is an extension of a relational repair construction algorithm while the other algorithm fragments the concrete instance to find the conflicts and leverages time intervals to build a repair. We have done some experiments on both temporal real-life data and synthetic data to compare the performance of our suggested algorithms for normalization and temporal repair construction. The results show that for real-life data, when the number of conflicts w.r.t. temporal functional dependencies is low (compared to the number of tuples in a relation), the algorithm that leverages time intervals is better."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Temporal Data Exchange and Repair"]}]}],"canonical_facts":{"dc:contributor":["Chomicki, Jan","Computer Science and Engineering"],"dc:creator":["Golshanara, Ladan"],"dc:date":["2018-10-26T02:57:08Z","2018","2018-08-10 14:03:18"],"dc:description":["Ph.D.","Temporal data isneeded by many organizations and individuals to support audit trails. With temporal data one can represent when a fact is true and for how long. The temporality offacts is also critical in diverse domains, from medical diagnosis toassessing the changing business conditions of companies to taxi and rental bicycle rides. To support temporal database applications suitable database features wererecently added to the SQL:2011 standard, and adopted by major database management systems such as DB2,Oracle, and Teradata.In today's digital world information about an entity can be found at different data sources at different times or in different versions of the same source. Despite the need for frameworks for temporal data curation tasks including temporal data cleaning, temporal data transformation, temporal data exchange and temporal data provenance, there are no principled frameworks in the literature. The goal of this research is to address the challenges that arise when one considers temporal data in the frameworks of data exchange and repair. The approach and the results can be used in other temporal data curation tasks as well. The frameworks are based on a formal two-tier view of temporal data consisting of the concrete view and the abstract view. There are two models to show a temporal database in the abstract view: snapshot model and timestamp model. In the snapshot model, temporal data is shown as an infinite sequence of snapshots. In the timestamp model each fact in the database is associated with every time point in which it is true. There may be infinitely many such points because the database may extend arbitrarily far into the future. In the concrete view each fact is associated with the time interval(s) in which it is true. The concrete view provides efficiency in storing and manipulating data. In the first part of this dissertation, we show how the framework of data exchange can be systematically extendedto temporal data. We first extend the chase procedure for the abstract view using the snapshot model to have a conceptual basis for the data exchange for temporal databases. Considering non-temporal source-to-target tuple generating dependencies and equality generating dependencies, the chase algorithm can be applied on each snapshot independently. Then we define a chase procedure (called c-chase) on concrete instances and show the result of c-chase on a concrete instance is semantically aligned with the result of chase on the corresponding abstract instance. In order to interpret intervals as constants while checking if a dependency or a query is satisfied by a concrete database, we will normalize the instance with respect to the dependency or the query. To obtain the semantic alignment, the nulls (which are introduced by data exchange and model incompleteness) in the concrete view are annotated with temporal information. Furthermore, we show that the result of the concrete chase provides a foundation for query answering. We define naive evaluation on the result of the c-chase and show it produces certain answers. The second part of the dissertation aims to investigate temporal repair checking with respect to temporal functional dependencies. Same as temporal data exchange framework, building on the relational notion of repair we have defined concrete repairs. We have also examined how a temporal repair checking algorithm can handle infinite abstract databases. We show how to reduce the problem of temporal repair checking on infinite temporal databases to the problem of temporal repair checking on finite temporal databases. We also develop two temporal repair construction algorithms: one is an extension of a relational repair construction algorithm while the other algorithm fragments the concrete instance to find the conflicts and leverages time intervals to build a repair. We have done some experiments on both temporal real-life data and synthetic data to compare the performance of our suggested algorithms for normalization and temporal repair construction. The results show that for real-life data, when the number of conflicts w.r.t. temporal functional dependencies is low (compared to the number of tuples in a relation), the algorithm that leverages time intervals is better."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78631"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["computer science"],"dc:title":["Temporal Data Exchange and Repair"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:14Z"}