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Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

Purpose: Evaluation of the reform of public policy of digital economy taxation in Ukraine under conditions of military threats.

Need of the Study: The global digital transformation of the economy gives the IT sector priority positions in shaping public policy goals. The world community is searching for optimal models of digital business taxation, which can enhance its global investment attractiveness. In 2021, Ukraine introduced new tax rules on digital services; however, the war launched on 24 February 2022 made irreversible changes for businesses. The Ukrainian government started a new special tax regime, whose impact on the business environment needs to be thoroughly studied.

Methodology: This research is based on the content analysis of the legal framework of state policy on taxation of digital economy services.

Findings: The authors found that the reforms in the taxation of digital economy services carried out in Ukraine are designed to create incentives for attracting foreign IT companies and can create an effective tax competitive advantage for our country. At the same time, the special facilitated tax regime for the period of martial law in Ukraine creates a certain buffer in counteracting the threatening economic consequences of the war in Ukraine.

Practical Implications: The study summarises major taxation amendments and special conditions under martial law in Ukraine that affect the development of the digital economy, which allows for assessing the consequences for the business environment in the national IT sector.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

In this study, the distinctive functional features of linked data (LD) catalogues were investigated to contrast with existing online public access catalogues (OPACs) and discovery systems using a checklist approach. The checklist was derived from a literature review and is composed of 10 items as follows: self-descriptive and dynamic content for resource description, linkage to external LD sources and online services, aggregation of knowledge contexts into knowledge graphs (KGs), URI-based link discovery, representation and query of LD relationships, URI-based serendipitous discovery, keyword recommendation, faceted limitation and browsing, visualization and openness of data.

Ten functional features derived from the literature were checked against existing LD catalogues offered by libraries, archives and museums (LAMs). The LD catalogues were regarded as qualified subjects if they offered functional features that were distinct from current OPACs and discovery systems through URI-based enrichment and aggregation from various LD sources. In addition to individual organizations, LD union catalogues were also included. However, LD hubs, such as ISNI, OCLC WorldCat Entities, VIAF and Wikidata, were excluded. In total, six LD catalogues from LAMs were selected as subjects for examination.

First, LD catalogues provide similar KG information through URI combination, and KGs also facilitate information serendipity, including social-document, intellectual, conceptual, spatial and temporal contexts and networks of corporate bodies, persons and families (CPFs). Second, LD catalogues have transformed the “seek first and browse later” paradigm into a “seek or browse” paradigm by refreshing the browsing function of traditional card catalogues with preview and new options to facilitate LD identification and discovery. Third, LD catalogues have refined keyword recommendation with the addition of the following fields: person’s title, CPF relationships, entity type and LD source. Lastly, a virtual union LD catalogue is offered.

The proposed checklist revealed the unique/improved functional features of LD catalogues, allowing further investigation and comparison. More cases from the fields of medicine, engineering science and so on will be required to make revisions to fine-tune the proposed checklist approach.

To the best of the author’s knowledge, this is the first study to propose a checklist of functional features for LD catalogues and examine what the results and features of LD catalogues have achieved and are supported by from ontologies across LAMs. The findings suggest that LD provides a viable alternative to catalogues. The proposed checklist and results pave the way for the future development of LD catalogues and next-generation catalogues and also provide a basis for the future study of LD catalogues from other fields to refine the proposed checklist.

The purpose of this paper is to understand how users behave and evaluate how systems with users are essential for interactive information retrieval (IIR) research. User study methodology serves as a primary approach to answering IIR research questions. In addition to designing user study procedures, understanding the limitations of varying study designs and discussing solutions to the limitations is also critical for improving the methods and advancing the knowledge in IIR.

Given this unresolved gap, we apply the faceted framework developed by Liu and Shah (2019) in systematically reviewing 131 IIR user studies recently published (2016–2021) on multiple IR and information science venues.

Our study achieve three goals: (1) extracting and synthesizing the reported limitations on multiple aspects of user study (e.g. recruitment, tasks, study procedures, system interfaces, data analysis methods) under associated facets; (2) summarizing the reported solutions to the limitations; (3) clarifying the connections between types of limitations and types of solutions.

The bibliography of user studies can be used by students and junior researchers who are new to user-centered IR studies as references for study design. Our results can facilitate the reflection and improvement on IR research methodology and serve as a checklist for evaluating customized IIR user studies in varying problem spaces.

To our knowledge, this work is the first study that systematically reviews the study limitations and solutions reported by IIR researchers in articles and empirically examines their connections to different study components.

Pb-free solders have been developed to replace the standard Sn–Pb eutectic solder since the prohibition on Pb used in solders. The Sn–Ag–Cu series of lead-free solders is the most extensively used in the electronics industry. The Ag₃Sn, which forms during isothermal ageing, can significantly degrade solder joint reliability. Sn–Ag–Cu solder’s high price further hindered its use in the electronics industry. This paper aims to investigate different copper percentages into Sn–xCu solder alloy to improve its microstructure and strength performance.

The solder alloys used in this work were Sn–xCu, where x = 0.0, 0.3, 0.5, 0.7, 1.0 Wt.%, which was soldered onto electroless nickel immersion gold (ENIG) substrate using carbon dioxide (CO₂) gas laser. Then these samples were subjected to isothermal aging for 0, 200, 500, 1,000 and 2,000 h. The Sn–xCu solder alloy was fabricated through a powder metallurgy process.

Microstructure characterization showed that Cu addition resulted in fine and rounded shape of Cu–Sn–Ni particles. Shear strength of Sn–xCu solder joints was increased with increasing Cu content, but at aging duration of 1,000 h, it dropped slightly. It is believed that the strength improved due to the increment of diffusion rate during isothermal aging.

In a Cu–Sn solder, the recommended amount is 1.0 Wt.% of Cu. In extensive aging procedures, it was discovered that Sn1.0Cu solder improved the reliability of solder joints. The findings indicated that the innovative solder alloys might satisfy the needs of high-reliability applications.

The study shows that the right amount of Cu enhances the solidification of Sn–Cu solder, increasing the shear force of the Cu–Sn solder joint. The Sn1.0Cu exhibits a ductile fracture on the top microstructure, improving the joint’s average shear strength.

This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.

The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.

Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.

The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.

This paper aims to explore the roles of psychologists in seclusion in adult mental health services in Ireland, their perspectives on seclusion and its use in recovery-oriented practice and related professional practice issues.

A qualitative hermeneutic phenomenological study was conducted from a social constructivist perspective. Semi-structured interviews with 17 psychologists were analysed using reflexive thematic analysis.

Twenty-four themes were identified, which were clustered into four overarching themes. Participants viewed themselves and psychology in Ireland more broadly as peripheral to seclusion. They believed that seclusion possessed no inherent therapeutic value but viewed it as an uncomfortable and multi-faceted reality. Participants regarded seclusion and recovery as largely inconsistent and difficult to reconcile, and they perceived systemic factors, which had a pervasive negative impact on seclusion and recovery in practice.

The findings highlight the perceived complexity of seclusion and its interface with recovery, and the need to conscientiously balance conflicting priorities that cannot be easily reconciled to ensure ethical practice. The findings suggest psychologists are well-suited to participate in local and national discussions on using seclusion in recovery-oriented practice.

This study offers a unique insight into psychologists’ perceptions of seclusion and considers the implications of these views. Participants’ nuanced views suggest that psychologists can make valuable contributions to local and national discussions on these topics.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.