Purpose-To present the state of the arts application of semantic web technologies in web portals and corresponding achievable improvements for identifying the potential improvement made by semantic web technology. Design/methodology/approach-An evaluation scheme is proposed to investigate various web portals that make use of semantic web technologies in order to identify their strengths and weaknesses. This scheme consists of three layers: information access, information processing and grounding technologies. Two academic portals and two commercial portals are selected based on the definition of semantic web portal. Detailed evaluation based on the proposed scheme is conducted on these four select portals. Findings-Semantic web technologies can definitely increase the information consistency and the information processing quality of web portals by using ontologies to model portal structure and consensus knowledge. Furthermore, semantic web services will be acting as the key technologies to lift current portals to next level. Originality/value-This paper proposes an elaborated evaluation method for investigating various portals. It reveals the current status of semantic web applications in web portals.

Background/Objectives: It is still a challenging issue to represent the reification effectively since the reification representation of RDF standard has been revealed some drawbacks.Methods/Statistical analysis: Currently, there are two main graph data models: RDF and LPG. LPG is a popular graph data model that is usually applied to NoSQL graph databases.This paper derives three types of the reification structures in terms of the structural and semantic relationships of the reification statements. The detailed representation of each type of the reification is presented with the extended LPG model.Findings: This paper proposes a novel approach to represent the reification structure of RDF from the perspective of LPG. The paper explores the formal, conceptual properties of the conventional LPG models and proposes their extension to capture more complex knowledge structures efficiently. These augmentations of LPG can achieve more efficient and flexible resource modeling. This paper derives three types of the reification structures in terms of the structural and semantic relationships of the reification statements: assertion, quantification, and entailment.The proposed approach not only preserves the structure and semantics of the reification but also enables LPG modeling of the complex structural statements to be easy and intuitive.This can contribute to transfer RDF graphs into LPGs.Improvements/Applications: The implementation of the extended LPG and the query processing of the reification remain future work.

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Background/Objectives: The mapping RDB to RDF has become important to populate Linked Data more efficiently. This paper shows how to implement SPARQL endpoint in RDB using a conceptual level mapping approach.Methods/Statistical analysis: Many diverse approaches and related languages for mapping RDB to RDF have been proposed. The prominent achievements of mapping RDB to RDF are two standard draft Direct Mapping and R2RML proposed by W3C RDB2RDF Working Group. This paper analyzes these conventional mapping approaches and proposes a new approach based on schema mapping. The paper also presents SPARQL query processing in RDB.Findings: There are distinct differences between instance level mapping and conceptual level mapping for RDB2RDF. Data redundancy of instance level mapping causes many inevitable problems during mapping procedure. The conceptual level mapping can provide straightforward and efficient way. The ER model in RDB and RDF model in Linked Data have obvious similarity. The ER model describes entities and relationships, which is the conceptual schema of RDB. RDF model consists of three parts: subject, predicate and object, which is the standard model for data interchange on the Web. The entities in ER model and subjects in RDF model are all the things that can be anything in the real world. Both the relationships in ER model and predicates in RDF model describe the relations between things.Since RDB and RDF share the similar modeling approach at the schema level, it is reasonable that mapping approach should be based on RDB schema. This kind of conceptual level mapping also can provide efficient SPARQL query processing in RDB.Improvements/Applications: The paper realizes SPARQL query processing in RDB, which is based on conceptual level mapping. The query experiments show that it is a concise and efficient way to populate Linked Data.

Background/Objectives: The vast amounts of high-quality data stored in relational databases (RDB) is the primary resources for Linked Open Data (LOD) datasets. This paper proposes a schema-based mapping approach from RDB to RDF, which provides succinct and efficient mapping.Methods/Statistical analysis: The various approaches, languages and tools for mapping RDB to LOD have been proposed in the recent years. This paper surveys and analyzes classic mapping approach and language such as Direct Mapping and R2RML. The mapping approaches can be categorized by means of their data modeling. After analyzing the conventional RDB-RDF mapping methods, this paper proposes a new mapping method and discusses its typical features and applications.Findings: There are two types of mapping approaches for the translation of RDB to RDF: instance-based and schema-based mapping approaches. The instance-based mapping approaches generate large amounts of RDF graphs by means of mapping rules. These approaches causes data redundancy since the same data is stored in two ways of RDB and RDF. It is very easy to bring the data inconsistence problem when data update operations occur. The schema-based mapping approaches can effectively avoid data redundancy since the mapping can be accomplished in the conceptual schema level.The architecture of SPARQL endpoint based on schema mapping approach consists of five phases:Generation of mapping description based on mapping rules.SPARQL query statements for RDF graph patterns.Translation of SPARQL query into SQL query.Execution of SQL query in RDB.Interpretation of SQL query result into JSON-LD format.Experiments show the schema-based mapping approach is a straightforward, succinct and efficient mapping method for RDB2RDF.Improvements/Applications: This paper proposes a schema-based mapping approach called R2RS, which shows better performance than the conventional mapping methods. In addition, R2RS also provides the efficient implementation of SPARQL endpoint in RDB.