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Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data.

This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP).

The applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach.

H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.

The purpose of this paper is to extract appropriate terms to summarize the current results in terms of the contents of textual facets. Faceted search on XML data helps users find necessary information from XML data by giving attribute–content pairs (called facet-value pair) about the current search results. However, if most of the contents of a facet have longer texts in average (such facets are called textual facets), it is not easy to overview the current results.

The proposed approach is based upon subsumption relationships of terms among the contents of a facet. The subsumption relationship can be extracted using co-occurrences of terms among a number of documents (in this paper, a content of a facet is considered as a document). Subsumption relationships compose hierarchies, and the authors utilize the hierarchies to extract facet-values from textual facets. In the faceted search context, users have ambiguous search demands, they expect broader terms. Thus, we extract high-level terms in the hierarchies as facet-values.

The main findings of this paper are the extracted terms improve users’ search experiences, especially in cases when the search demands are ambiguous.

An originality of this paper is the way to utilize the textual contents of XML data for improving users’ search experiences on faceted search. The other originality is how to design the tasks to evaluate exploratory search like faceted search.

XML has become a standard data format for many applications and efficient retrieval methods are required. Typically, there are roughly two kinds of retrieval methods, namely path‐based method (e.g. XPath and XQuery) and keyword search, but these methods do not work when users do not have any concrete information need. To expand feasibility of XML data retrieval is an important task and this is the purpose of this paper.

The paper's strategy is to apply faceted navigation for XML data. Faceted navigation is an exploratory search which enables the exploration of data making use of attributes, called facets. General faceted navigation methods are applied for attributed objects but XML data have no criteria because XML nodes are objects and facets. Thus, the paper's approach is to construct a framework to enable faceted navigation over XML data. It first extracts objects based on occurrence of nodes and facets. Then it constructs a faceted navigation interface for extracted objects and facets.

The framework achieves semi‐automatic construction of faceted navigation interface from an XML database. In the experiments, the show feasibility of the framework is shown by three faceted navigation interfaces using existing real XML data. On the other hand, the user study shows the retrieval method helps users to find required information.

There are only a few works which apply faceted navigation for XML data and these works are based on predefined objects and facets which need human effort. In contrast, this framework needs human decision making only when choosing objects and facets to be used in the faceted navigation interface.