{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"id":[{"id":"https:\/\/ror.org\/03mb6wj31","id-type":"ROR","asserted-by":"publisher"},{"id":"https:\/\/www.isni.org\/000000041937028X","id-type":"ISNI","asserted-by":"publisher"},{"id":"https:\/\/www.wikidata.org\/entity\/Q1640731","id-type":"wikidata","asserted-by":"publisher"}],"name":"Universitat Polit\u00e8cnica de Catalunya","acronym":["UPC"]}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:38:16Z","timestamp":1785436696131,"version":"3.56.0"},"reference-count":0,"publisher":"Universitat Polit\u00e8cnica de Catalunya","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Over the last decade, we have witnessed the emergence of networks in a wide spectrum of application domains, ranging from social and information networks to biological and transportation networks.\r\nGraphs provide a solid theoretical foundation for modeling complex networks, and revealing valuable insights from both the network structure and the data embedded within its entities.\r\nAs the business and social environments are getting increasingly complex and interconnected, graphs became a widespread abstraction at the core of the information infrastructure supporting those environments. Modern information systems consist of a large number of sophisticated and interacting business entities that naturally form graphs. In particular, integrating graphs into data warehouse systems received a lot of interest from both academia and industry. Indeed, data warehouses are the central enterprise's information repository, and are critical for proper decision support and future planning. Graph warehousing is emerging as the field that extends current information systems with graph management and analytics capabilities. Many approaches were proposed to address the graph data warehousing challenge. These efforts laid the foundation for multidimensional modeling and analysis of graphs. However, most of the proposed approaches partially tackle the graph warehousing problem by being restricted to simple abstractions such as homogeneous graphs or ignoring important topics such as multidimensional integrity constraints and dimension hierarchies.\r\n\r\nIn this dissertation, we conduct a systematic study of the graph data warehousing topic, and address the key challenges of database and multidimensional modeling of graphs.\r\nWe first propose GRAD, a new graph database model specifically tuned for warehousing and OLAP analytics. GRAD aims to provide analysts with a set of simple, well-defined, and adaptable conceptual components to support rich semantics and perform complex analysis on graphs.\r\nThen, we define the multidimensional concepts for heterogeneous attributed graphs and highlight the new types of measures that could be derived. We project this multidimensional model on property graphs and explore how to extract the candidate multidimensional concepts and build graph cubes. Then, we extend the multidimensional model by integrating GRAD and show how graph modeling based on GRAD facilitates multidimensional modeling, and enables  supporting dimension hierarchies and building new types of OLAP cubes on graphs.\r\nAfterwards, we present TopoGraph, a graph data warehousing framework that extends current graph warehousing models with new types of cubes and queries combining graph-oriented and OLAP querying. TopoGraph goes beyond traditional OLAP cubes, which process value-based grouping of tables, by considering in addition the topological properties of the graph elements. And it goes beyond current graph warehousing models by proposing new types of graph cubes. These cubes embed a rich repertoire of measures that could be represented with numerical values, with entire graphs, or as a combination of them.\r\nFinally, we propose an architecture of the graph data warehouse and describe its main building blocks and the remaining gaps. The various components of the graph warehousing framework can be effectively leveraged as a foundation for designing and building industry-grade graph data warehouses.\r\n\r\nWe believe that our research in this thesis brings us a step closer towards a better understanding of graph warehousing. Yet, the models and framework we proposed are the tip of the iceberg.  The marriage of graph and warehousing technologies will bring many exciting research opportunities, which we briefly discuss at the end of the thesis.<\/jats:p>\n                <jats:p>Durant l\u2019\u00faltima d\u00e8cada, hem estat testimonis de l\u2019aparici\u00f3 de xarxes en un ampli espectre de dominis d\u2019aplicaci\u00f3, que van de les xarxes socials i d\u2019informaci\u00f3 a xarxes biol\u00f2giques i de transport. Els grafs proporcionen un fonament te\u00f2ric s\u00f2lid per a modelar xarxes complexes i revelen informaci\u00f3 valuosa tant de l'estructura de la xarxa com de les dades integrades a les seves entitats. A mesura que els entorns empresarials i socials s\u00f3n cada cop m\u00e9s complexos i interconnectats, els grafs es van convertir en una abstracci\u00f3 generalitzada en el nucli de la infraestructura d'informaci\u00f3 que dona suport a aquests entorns. Els sistemes d'informaci\u00f3 moderns consisteixen en un gran nombre d'entitats empresarials i la seva interacci\u00f3, que formen grafs de forma natural. En particular, la integraci\u00f3 de grafs en sistemes de magatzem de dades va rebre molt d\u2019inter\u00e8s tant de l\u2019\u00e0mbit acad\u00e8mic com de la ind\u00fastria. De fet, els magatzems de dades s\u00f3n el repositori central d'informaci\u00f3 de l'empresa i s\u00f3n fonamentals per a un suport adequat a la presa de decisions i una planificaci\u00f3 futura. Els magatzems de dades en graf (graph data warehousing) \u00e9s un camp emergent que est\u00e9n els sistemes d\u2019informaci\u00f3 tradicionals amb capacitats d\u2019administraci\u00f3 i d\u2019an\u00e0lisi de dades en format grafs. Fins ara, s'han proposat molts enfocaments per afrontar el repte de l'emmagatzematge de dades en graf. Aquests esfor\u00e7os van posar els fonaments pel modelatge i l'an\u00e0lisi de grafs d'una perspectiva multidimensional. Tanmateix, la majoria dels plantejaments proposats aborden parcialment el problema de l'emmagatzematge de grafs restringint-se a abstraccions simples com ara grafs homogenis o ignorant temes importants com ara restriccions d\u2019integritat multidimensionals i jerarquies de dimensi\u00f3. En aquesta tesi realitzem un estudi sistem\u00e0tic del tema d'emmagatzematge de dades en graf i tractem els reptes clau de la base de dades i el modelatge multidimensional de grafs. Primer proposem GRAD, un nou model de base de dades de grafs espec\u00edficament ajustat per a emmagatzematge i anal\u00edtica OLAP. GRAD pret\u00e9n proporcionar als analistes un conjunt de components conceptuals simples, ben definits i adaptables per donar suport a elements sem\u00e0ntics complexos i realitzar an\u00e0lisis complexos sobre grafs. A continuaci\u00f3, definim els conceptes multidimensionals per a grafs heterogenis amb atributs i ressaltem els nous tipus de mesures que es poden derivar. Projectem aquest model multidimensional en property graphs i explorem com extreure conceptes multidimensionals candidats i construir cubs de grafs. A continuaci\u00f3, ampliem el model multidimensional integrant GRAD i mostrem com el modelatge de grafs basat en GRAD facilita el modelatge multidimensional i permet suportar jerarquies de dimensions i crear nous tipus de cubs OLAP en grafs. Despr\u00e9s, presentem TopoGraph, un marc d\u2019emmagatzematge de dades en graf que amplia els models d\u2019emmagatzematge de grafs actuals amb nous tipus de cubs i consultes que combinen la consulta orientada a grafs i OLAP. TopoGraph va m\u00e9s enll\u00e0 dels cubs tradicionals OLAP, que processen l'agrupaci\u00f3 de taules basada en el valor, considerant a m\u00e9s les propietats topol\u00f2giques dels grafs. I va m\u00e9s enll\u00e0 dels models d\u2019emmagatzematge en graf actuals proposant nous tipus de cubs de grafs. Aquests cubs incorporen un ric repertori de mesures que es podrien representar amb valors num\u00e8rics, amb grafs sencers o com a combinaci\u00f3 d\u2019aquests. Finalment, proposem una arquitectura per al magatzem de dades en graf i descrivim els blocs de construcci\u00f3 principals i els buits restants. Els diversos components del marc d'emmagatzematge de grafs es poden aprofitar efica\u00e7ment com a base per dissenyar i construir magatzems de dades de grafs a nivell industrial. Creiem que la nostra recerca en aquesta tesi ens apropa un pas m\u00e9s cap a una millor comprensi\u00f3 de graph warehousing.<\/jats:p>","DOI":"10.5821\/dissertation-2117-352210","type":"dissertation","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T01:25:08Z","timestamp":1732152308000},"approved":{"date-parts":[[2020,10,29]]},"source":"Crossref","is-referenced-by-count":0,"title":["Graph data warehousing"],"prefix":"10.5821","author":[{"given":"Amine","family":"Ghrab","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3865","container-title":[],"original-title":[],"contributor":[{"sequence":"additional","affiliation":[],"role":[null]}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T06:42:23Z","timestamp":1769668943000},"score":1,"resource":{"primary":{"URL":"https:\/\/hdl.handle.net\/2117\/352210"}},"subtitle":[],"editor":[{"given":"\u00d3scar","family":"Romero Moral","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]},{"given":"Esteban","family":"Zimanyi Borrageiros","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[null]]},"references-count":0,"URL":"https:\/\/doi.org\/10.5821\/dissertation-2117-352210","relation":{},"subject":[]}}