In recent years we have seen significant advances in the technology used to both publish and consume Linked Data. However, in order to support the next generation of ebusiness applications on top of interlinked machine readable data suitable forms of access control need to be put in place. Although a number of access control models and frameworks have been put forward, very little research has been conducted into the security implications associated with granting access to partial data or the correctness of the proposed access control mechanisms. Therefore the contributions of this paper are two fold: we propose a query rewriting algorithm which can be used to partially restrict access to SPARQL 1.1 queries and updates; and we demonstrate how a set of criteria, which was originally used to verify that an access control policy holds over different database states, can be adapted to verify the correctness of access control via query rewriting.
Linked Data Fragments (LDFs) refer to Web interfaces that allow for accessing and querying Knowledge Graphs on the Web. These interfaces, such as SPARQL endpoints or Triple Pattern Fragment servers, differ in the SPARQL expressions they can evaluate and the metadata they provide. Client-side query processing approaches have been proposed and are tailored to evaluate queries over individual interfaces. Moreover, federated query processing has focused on federations with a single type of LDF interface, typically SPARQL endpoints. In this work, we address the challenges of SPARQL query processing…
In the distributed and dynamic framework of the Web, data quality is a big challenge. The Linked Open Data (LOD) provides an enormous amount of data, the quality of which is difficult to control. Quality is intrinsically a matter of usage, so consumers need ways to specify quality rules that make sense for their use, in order to get only data conforming to these rules. We propose a user-side query framework equipped with a checker of constraints and confidence levels on data resulting from LOD providers\' query evaluations. We detail its theoretical foundations and we provide experimental resu…
As RDF becomes more widely established and the amount of linked data is rapidly increasing, the efficient querying of large amount of data becomes a significant challenge. In this paper, we propose a family of algorithms for querying large amount of linked data in a distributed manner. These query evaluation algorithms are independent of the way the data is stored, as well as of the particular implementation of the query evaluation. We then use the MapReduce paradigm to present a distributed implementation of these algorithms and experimentally evaluate them, although the algorithms could be s…
An increasing number of organisations in almost all fields have started adopting semantic web technologies for publishing their data as open, linked and interoperable (RDF) datasets, queryable through the SPARQL language and protocol. Link traversal has emerged as a SPARQL query processing method that exploits the Linked Data principles and the dynamic nature of the Web to dynamically discover data relevant for answering a query by resolving online resources (URIs) during query evaluation. However, the execution time of link traversal queries can become prohibitively high for certain query typ…
The SPARQL2XQuery Interoperability Framework. Utilizing Schema Mapping, Schema Transformation and Query Translation to Integrate XML and the Semantic Web
Web of Data是一个开放的环境，由来自不同领域的大量相互链接的大型RDF数据集组成。在这种环境中，组织和公司采用利用语义Web（SW）技术的关联数据实践，以便发布他们的数据并提供SPARQL端点（即，基于SPARQL的搜索服务）。另一方面，当今Web中信息交换的主导标准是XML。SW和XML世界及其开发的基础设施基于不同的数据模型、语义和查询语言。因此，至关重要的是开发互操作性机制，允许Web of Data用户从他们自己的工作环境中使用SPARQL访问XML数据集。期望所有现有的遗留数据（例如，关系、XML等）将转换为软件数据。因此，将遗留数据发布为关联数据并在其上提供SPARQL端点已成为一个主要的研究挑战。在这个方向上，我们引入了SPARQL 2XQuery框架，它创建了一个可互操作的环境，SPARQL查询自动转换为XQuery查询，以便在Web上访问XML数据。SPARQL 2XQuery框架为OWL-RDF/S到XML Schema映射的表达提供了一个映射模型，也为SPARQL到XQuery的转换提供了一种方法。为此，我们的框架支持本体和XML模式之间的手动和自动映射规范。在自动映射规范场景中，SPARQL 2XQuery利用将XML模式转换为OWL本体的XS 2 OWL组件。最后，进行了大量的实验，以评估模式转换，映射生成，查询翻译和查询评估效率，使用真实和合成…
Relational query optimisers rely on cost models to choose between different query execution plans. Selectivity estimates are known to be a crucial input to the cost model. In practice, standard selectivity estimation procedures are prone to large errors. This is mostly because they rely on the so-called attribute value independence and join uniformity assumptions. Therefore, multidimensional methods have been proposed to capture dependencies between two or more attributes both within and across relations. However, these methods require a large computational cost which makes them unusable in pr…
Today's international corporations such as BASF, a leading company in the crop protection industry, produce and consume more and more data that are often fragmented and accessible through Web APIs. In addition, part of the proprietary and public data of BASF's interest are stored in triple stores and accessible with the SPARQL query language. Homogenizing the data access modes and the underlying semantics of the data without modifying or replicating the original data sources become important requirements to achieve data integration and interoperability. In this work, we propose a federated dat…
In ontology-based data access, multiple data sources are integrated using an ontology and mappings. In practice, this is often achieved by a bootstrapping process, that is, the ontology and mappings are first designed to support only the most important queries over the sources and then gradually extended to enable additional queries. In this paper, we study two reasoning problems that support such an approach. The expressibility problem asks whether a given source query $q_s$ is expressible as a target query (that is, over the ontology's vocabulary) and the verification problem asks, additiona…
We present bundled references, a new building block to provide linearizable range query operations for highly concurrent lock-based linked data structures. Bundled references allow range queries to traverse a path through the data structure that is consistent with the target atomic snapshot. We demonstrate our technique with three data structures: a linked list, skip list, and a binary search tree. Our evaluation reveals that in mixed workloads, our design can improve upon the state-of-the-art techniques by 1.2x-1.8x for a skip list and 1.3x-3.7x for a binary search tree. We also integrate our…
The recent advancements of the Semantic Web and Linked Data have changed the working of the traditional web. There is significant adoption of the Resource Description Framework (RDF) format for saving of web-based data. This massive adoption has paved the way for the development of various centralized and distributed RDF processing engines. These engines employ various mechanisms to implement critical components of the query processing engines such as data storage, indexing, language support, and query execution. All these components govern how queries are executed and can have a substantial e…
Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets, either by materializing integrated data into RDF or by performing on-the fly querying via SPARQL query translation. In the specific case of tabular datasets represented as several CSV or Excel files, query translation approaches have been applied by considering each source as a single table that can be loaded into a relational database management system (RDBMS). Nevertheless, constraints over these tables are not represented; thus, neither consistency among attributes nor indexes …
Islamic Azad University（伊斯兰阿扎德大学）；Mobile Telecommunication Company of Iran（伊朗移动电信公司）；Iran University of Medical Sciences（伊朗医科大学）；University of Human Development（人类发展大学）；Gachon University（加川大学）；Technische Universität Dresden（德累斯顿工业大学）
Access plan recommendation is a query optimization approach that executes new queries using prior created query execution plans (QEPs). The query optimizer divides the query space into clusters in the mentioned method. However, traditional clustering algorithms take a significant amount of execution time for clustering such large datasets. The MapReduce distributed computing model provides efficient solutions for storing and processing vast quantities of data. Apache Spark and Apache Hadoop frameworks are used in the present investigation to cluster different sizes of query datasets in the Map…
Traditional data systems require specialized technical skills where users need to understand the data organization and write precise queries to access data. Therefore, novice users who lack technical expertise face hurdles in perusing and analyzing data. Existing tools assist in formulating queries through keyword search, query recommendation, and query auto-completion, but still require some technical expertise. An alternative method for accessing data is Query by Example (QBE), where users express their data exploration intent simply by providing examples of their intended data. We study a s…
