1. |
- Lambrix, Patrick, Professor, 1965-, et al.
(författare)
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The materials design ontology
- 2024
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Ingår i: Semantic Web. - : IOS Press. - 1570-0844 .- 2210-4968. ; 15:2, s. 481-515
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Tidskriftsartikel (refereegranskat)abstract
- In the materials design domain, much of the data from materials calculations is stored in different heterogeneous databases with different data and access models. Therefore, accessing and integrating data from different sources is challenging. As ontology-based access and integration alleviates these issues, in this paper we address data access and interoperability for computational materials databases by developing the Materials Design Ontology. This ontology is inspired by and guided by the OPTIMADE effort that aims to make materials databases interoperable and includes many of the data providers in computational materials science. In this paper, first, we describe the development and the content of the Materials Design Ontology. Then, we use a topic model-based approach to propose additional candidate concepts for the ontology. Finally, we show the use of the Materials Design Ontology by a proof-of-concept implementation of a data access and integration system for materials databases based on the ontology.
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2. |
- Li, Huanyu, 1992-, et al.
(författare)
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OBG-gen: Ontology-Based GraphQL Server Generation for Data Integration
- 2023
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Ingår i: Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice.
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Konferensbidrag (refereegranskat)abstract
- A GraphQL server contains two building blocks: (1) a GraphQL schema defining the types of data objects that can be requested; (2) resolver functions fetching the relevant data from underlying data sources. GraphQL can be used for data integration if the GraphQL schema provides an integrated view of data from multiple data sources, and the resolver functions are implemented accordingly.However, there does not exist a semantics-aware approach to use GraphQL for data integration.We proposed a framework using GraphQL for data integration in which a global domain ontology informs the generation of a GraphQL server. Furthermore, we implemented a prototype of this framework, OBG-gen. In this paper, we demonstrate OBG-gen in a real-world data integration scenario in the materials design domain and in a synthetic benchmark scenario.
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3. |
- Li, Huanyu, 1992-, et al.
(författare)
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Ontology-based GraphQL server generation for data access and data integration
- 2024
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Ingår i: Semantic Web. - : IOS Press. - 1570-0844 .- 2210-4968. ; , s. 1-37
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Tidskriftsartikel (refereegranskat)abstract
- In a GraphQL Web API, a so-called GraphQL schema defines the types of data objects that can be queried, and so-called resolver functions are responsible for fetching the relevant data from underlying data sources. Thus, we can expect to use GraphQL not only for data access but also for data integration, if the GraphQL schema reflects the semantics of data from multiple data sources, and the resolver functions can obtain data from these data sources and structure the data according to the schema. However, there does not exist a semantics-aware approach to employ GraphQL for data integration. Furthermore, there are no formal methods for defining a GraphQL API based on an ontology.In this work, we introduce a framework for using GraphQL in which a global domain ontology informs the generation of a GraphQL server that answers requests by querying heterogeneous data sources.The core of this framework consists of an algorithm to generate a GraphQL schema based on an ontology and a generic resolver function based on semantic mappings. We provide a prototype, OBG-gen, of this framework, and we evaluate our approach over a real-world data integration scenario in the materials design domain and two synthetic benchmark scenarios (Linköping GraphQL Benchmark and GTFS-Madrid-Bench). The experimental results of our evaluation indicate that: (i) our approach is feasible to generate GraphQL servers for data access and integration over heterogeneous data sources, thus avoiding a manual construction of GraphQL servers, and (ii) our data access and integration approach is general and applicable to different domains where data is shared or queried via different ways.
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4. |
- Li, Huanyu, 1992-
(författare)
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Ontology-Driven Data Access and Data Integration with an Application in the Materials Design Domain
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The Semantic Web aims to make data on the web machine-readable by introducing semantics to the data. Ontologies are one of the critical technologies in the Semantic Web. Ontologies, which provide a formal definition of a domain of interest, can play an important role in enabling semantics-aware data access and data integration over heterogeneous data sources. Traditionally, ontology-based data access and integration methods focus on data that follows relational data models. However, in some domains, such as materials design, the models that data follows and the methods by which it is shared differ today. Data may be based on different data models (i.e., relational models and non-relational models) and may be shared in different ways (e.g., as tabular data via SQL queries or API (Application Programming Interface) requests, or as JSON-formatted data via API requests). To address these challenges, conventional ontology-based data access and integration approaches must be adapted. The recently developed GraphQL, a framework for building APIs, is an interesting candidate for providing such an approach, although the use of GraphQL for integration has not yet been studied.In this thesis, we propose a GraphQL-based framework for data access and integration. As part of this framework, we propose and implement a novel approach that enables automatic generation of GraphQL servers based on ontologies rather than building them from scratch. The framework is evaluated via experiments based on a synthetic benchmark dataset. Further, we utilize the field of materials design as a target domain to evaluate the feasibility of our framework by showing the use of the framework for the Open Databases Integration for Materials Design (OPTIMADE), which is a community effort aiming to develop a specification for a common API to make materials databases interoperable. At the beginning of this work, no ontologies existed for the domain of computational materials databases. As our approach requires the use of an ontology, we developed one: the Materials Design Ontology (MDO). Furthermore, when new databases are added or new kinds of data are added to existing databases, the coverage of the ontology driving the GraphQL server generation may need to be enlarged. Therefore, we study how ontologies can be extended and propose an approach based on phrase-based topic modeling, formal topical concept analysis and domain expert validation. In addition to extending MDO, we also use this approach to extend two ontologies in the nanotechnology domain.
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5. |
- Acosta, Maribel, et al.
(författare)
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Federated RDF query processing
- 2019
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Ingår i: Encyclopedia of big data technologies. - Cham : Springer. - 9783319639628
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Bokkapitel (refereegranskat)abstract
- Federated RDF query processing is concerned with querying a federation of RDF data sources where the queries are expressed using a declarative query language (typically, the RDF query language SPARQL), and the data sources are autonomous and heterogeneous. The current literature in this context assumes that the data and the data sources are semantically homogeneous, while heterogeneity occurs at the level of data formats and access protocols.
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6. |
- Cheng, Sijin, et al.
(författare)
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A Cost Model to Optimize Queries over Heterogeneous Federations of RDF Data Sources
- 2023
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Ingår i: Joint Proceedings of the ESWC 2023 Workshops and Tutorials co-located with 20th European Semantic Web Conference (ESWC 2023).
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Konferensbidrag (refereegranskat)abstract
- Federated processing of queries over RDF data sources offers significant potential when a SPARQL query cannot be answered by a single data source alone. However, finding efficient plans to execute a queryover a federation is challenging, especially if different federation members provide different types of data access interfaces. Different interfaces imply different request types, different forms of responses, and different physical algorithms that can be used, each of which consumes varying amounts of resources during query execution. This heterogeneity poses additional obstacles to the task of planning query executions, in addition to the inherent complexity arising from numerous possible join orderings andvarious physical algorithms. As a first step to address these challenges, we propose a cost model that captures the resource requirements of different operators depending on the type of federation member,allowing us to estimate cost of a given query execution plan without actually executing it. To evaluate our approach, we conduct experiments on FedBench with our cost model and compare it to the current state-of-the-art approach to query planning for heterogeneous federations of RDF data sources.
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7. |
- Cheng, Sijin, et al.
(författare)
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Considering Vocabulary Mappings in Query Plans for Federations of RDF Data Sources
- 2023
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Ingår i: Proceedings of the 29th International Conference on Cooperative Information Systems (CoopIS).
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Konferensbidrag (refereegranskat)abstract
- Federations of RDF data sources oer great potential for queries that cannot be answered by a single data source. However, querying such federations poses several challenges, one of which is that different but semantically-overlapping vocabularies may be used for the respective RDF data. Since the federation members usually retain their autonomy, this heterogeneity cannot simply be homogenized by modifying the data in the data sources. Therefore, handling this heterogeneity becomes a critical aspect of query planning and execution. We introduce an approach to address this challenge by leveraging vocabulary mappings for the processing of queries over federations with heterogeneous vocabularies. This approach not only translates SPARQL queries but also preserves the correctness of results during query execution. We demonstrate the effectiveness of the approach and measure how the application of vocabulary mappings affects on the performance of federated query processing.
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8. |
- Cheng, Sijin, et al.
(författare)
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FedQPL: A Language for Logical Query Plans over Heterogeneous Federations of RDF Data Sources
- 2020
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Ingår i: iiWAS '20: The 22nd International Conference on Information Integration and Web-based Applications & Services, Virtual Event / Chiang Mai, Thailand, November 30 - December 2, 2020. - New York, NY, United States : Association for Computing Machinery (ACM).
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Konferensbidrag (refereegranskat)abstract
- Federations of RDF data sources provide great potential whenqueried for answers and insights that cannot be obtained from one data source alone. A challenge for planning the execution of queries over such a federation is that the federation may be heterogeneous in terms of the types of data access interfaces provided by the federation members. This challenge has not received much attention in the literature. This paper provides a solid formal foundation for future approaches that aim to address this challenge. Our main conceptual contribution is a formal language for representing query execution plans; additionally, we identify a fragment of this language that can be used to capture the result of selecting relevant data sources for different parts of a given query. As technical contributions, we show that this fragment is more expressive than what is supported by existing source selection approaches, which effectively highlights an inherent limitation of these approaches.Moreover, we show that the source selection problem is NP-hard and in ΣP2 , and we provide a comprehensive set of rewriting rules that can be used as a basis for query optimization.
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9. |
- Cheng, Sijin, et al.
(författare)
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LinGBM: A Performance Benchmark for Approaches to Build GraphQL Servers
- 2022
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Ingår i: Web Information Systems Engineering – WISE 2022. - Cham : Springer. - 9783031208904 - 9783031208911 ; , s. 209-224
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Konferensbidrag (refereegranskat)abstract
- GraphQL is a popular new approach to build Web APIs that enable clients to retrieve exactly the data they need. Given the growing number of tools and techniques for building GraphQL servers, there is an increasing need for comparing how particular approaches or techniques affect the performance of a GraphQL server. To this end, we present LinGBM, a GraphQL performance benchmark to experimentally study the performance achieved by various approaches for creating a GraphQL server. In this paper, we discuss the design considerations of the benchmark and describe its main components (data schema; query templates; performance metrics). Thereafter, we present experimental results obtained by applying the benchmark in two different use cases, which demonstrate the broad applicability of LinGBM.
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10. |
- Cheng, Sijin, 1993-
(författare)
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Query Processing over Heterogeneous Federations of Graph Data
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Graph data offers a natural and intuitive way to represent complex relationships in various real-world phenomena, such as social networks, e-commerce platforms, and biological networks. The way we interact with information, technology and even society has been changed by graph data, especially after Google started in 2012 to develop the so-called Knowledge Graph. A federation of Knowledge Graphs allows users to perform queries that span across multiple Knowledge Graphs, enabling them to discover relationships and insights that would not be apparent within a single isolated graph and to understand complex knowledge by considering information from different domains or sources. However, retrieving information from such a federation also comes with challenges that must be addressed. Motivated by issues related to retrieving information from federations of Knowledge Graphs, in this thesis, we focus on Knowledge Graphs represented in the Resource Description Framework (RDF) and two forms of heterogeneity: the heterogeneity in terms of data access interfaces, and the heterogeneity of vocabulary used in the schema of RDF data sources. Our research deals with these complexities by designing query planning and optimization to bridge the gap between different graph data sources.In this thesis, we first focus on federations that are heterogeneous in terms of data access interfaces. In particular, we establish a formal framework for defining and representing query plans over heterogeneous federations of graph data. We introduce a data model that captures the notion of a heterogeneous federation of RDF data sources. Based on this model, we define a language, called FedQPL, that can be used to describe logical query plans formally. More precisely, this language can be applied both to define query planning and optimization approaches in a more precise manner and to represent the logical plans in a query engine. Thereafter, we provide an extensive set of rewriting rules together with a cost model for optimization. A comprehensive experimental evaluation shows that the query plan selected using our cost model requires less data to be transferred compared to the baseline approach.Then, this thesis addresses the heterogeneity of vocabularies used in the schema of RDF data sources by extending FedQPL with vocabulary awareness. To this end, we first define what the expected result of a query in a vocabulary-aware setting is; then, we introduce two new query plan operators to translate solutions from a local to the global vocabulary and vice versa; and finally, we introduce an algorithm that produces correct, vocabulary-aware query plans. To identify the overhead of considering vocabulary mappings during query processing, we evaluate our approach in federations with different vocabulary mapping scenarios. Our experiments show that there is no overhead in planning time when considering vocabulary mappings; however, it takes slightly longer to execute the queries than in a baseline scenario with materialized mapped data. In addition, we also provide a set of rewriting rules specific to vocabulary-aware FedQPL expressions, which can be used as query rewriting rules for query optimization under various conditions. Experimental evaluations support the hypothesis that rewriting rules can significantly improve query processing performance while decreasing the amount of extra work introduced by considering vocabulary mappings.Furthermore, we explore possibilities of integrating other types of graph data sources (specifically GraphQL) into the federation. To better understand the different implementation techniques of GraphQL, we design a GraphQL performance benchmark to thoroughly evaluate and compare the performance of approaches to creating GraphQL servers, as a preparation for future integration of Knowledge Graphs that can be accessed via GraphQL APIs into our federation.
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