Data and information management最新文献

{"title":"Open access data policies and technologies: Introduction to special issue","authors":"Di Wang,&nbsp;Misita Anwar,&nbsp;Rong Tang","doi":"10.1016/j.dim.2025.100093","DOIUrl":"10.1016/j.dim.2025.100093","url":null,"abstract":"<div><div>This special issue of the journal “Data and Information Management” looks into the global development of open access data (OAD) from the perspectives of policies and technologies. The papers included in this issue explore barriers and factors for OAD practices, identify policy gaps, and propose technological solutions to improve data accessibility and interoperability. This introduction situates these contributions within broader discussions of the evolving landscape of OAD, highlights its societal and economic benefits, and identifies future directions for studies of OAD policies and technologies to advance practices globally for a more sustainable and equal OAD ecosystem.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"9 1","pages":"Article 100093"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying factors and configurations influencing the effectiveness of government data openness in China based on fsQCA","authors":"Xu Chen,&nbsp;Muhua Hu","doi":"10.1016/j.dim.2024.100071","DOIUrl":"10.1016/j.dim.2024.100071","url":null,"abstract":"<div><div>Engaging government data openness is of great significance to economic development and social services. As the government data openness process continues to deepen in China, it is worth studying the factors that affect government data openness and the development paths leading to the high performance of data opening. Based on the Technology-Organization-Environment (TOE) theory, this paper proposes a government data open analysis framework including five condition variables (i.e., data support, technical support, government support, economic development, and social development). Using Fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze data from 25 provincial governments, we discover the key influencing factors and configurations leading to high-level and non-high-level data openness. Experimental results show that a single factor does not determine the level of government data opening. Instead, it is jointly affected by multiple factors in technology, organization, and environment. Three configuration paths are found in developing China’s provincial government data openness, including technology-environment-driven, technology-organization-environment-driven, and technology-organization-driven modes. The analysis results of this paper provide inspiration and suggestions for provincial governments to improve the level of government data opening according to local characteristics.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"9 1","pages":"Article 100071"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140400196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding barriers affecting the adoption and usage of open access data in the context of organizations","authors":"Murat Tahir Çaldağ ,&nbsp;Ebru Gökalp","doi":"10.1016/j.dim.2023.100049","DOIUrl":"10.1016/j.dim.2023.100049","url":null,"abstract":"<div><div>Data and information are growing exponentially due to advances and innovations in information and communication technologies. This growth forces organizations to gain new capabilities to compete or stay current in their marketplace. Open Access Data (OAD), resulting from the open source movement, is seen as a double-edged sword from the management perspective. It can potentially provide enormous social and economic value, such as transparency, participation culture, innovativeness, and accountability to organizations, governments, and, more importantly, citizens. Although the benefits of organizational adoption are significant, most OAD-related projects fail cause of organizational barriers and resistance to adoption. This study first aims to find these organizational barriers on adopting OAD to raise awareness of the obstacles organizations must overcome. Towards this aim, after conducting a systematic literature review (SLR) and an expert panel, a research model based on the Technology – Organization – Environment (TOE) framework is proposed in this study. As a result of SLR, 97 barriers were identified from ten primary studies. After critically examining these barriers, a research model classifying 22 crucial barriers to organizational OAD adoption based on the TOE framework is proposed. Another significant contribution of this study is to draw attention to under-researched barriers in the literature, such as Power and Control, Political Commitment, Inter-Organizational Trust, IT Governance, and Competitive Pressure.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"9 1","pages":"Article 100049"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metadata application profile as a mechanism for semantic interoperability in FAIR and open data publishing","authors":"Nishad Thalhath,&nbsp;Mitsuharu Nagamori,&nbsp;Tetsuo Sakaguchi","doi":"10.1016/j.dim.2024.100068","DOIUrl":"10.1016/j.dim.2024.100068","url":null,"abstract":"<div><div>Application profiles, also known as metadata application profiles, are customised collections of vocabularies adapted from various namespaces and tailored for specific local applications. These profiles act as constrainers and explainers for the (meta)data. Semantic interoperability is the ability of computer systems to exchange data in a mutually understandable manner, facilitating data sharing across diverse platforms and applications without compromising its meaning. As a critical component of semantic interoperability, application profiles enforce semantics to (meta)data, enhancing its openness, interoperability, and reusability. This study assesses the feasibility of representing a comprehensive application profile in a format aligned with the semantic web, ensuring interoperability between profiles and datasets. Dublin Core Description Set Profiles (DSP) is adapted as the modeling framework for metadata application profiles, steering the associated datasets toward RDF compliance. The research outcomes include “Yet Another Metadata Application Profiles” (YAMA) as a preprocessor grounded in the DSP framework for developing and managing metadata application profiles. YAMA facilitates the generation of various standard formats of application profiles, ensuring they are represented in human-readable documentation, machine-actionable forms, and even data validation languages. A data mapping extension to YAMA is proposed to ensure the semantic interoperability of open data, bridging non-RDF data structures to RDF, thus enabling the publication of 5-star open data. This ensures smooth dataset integration and the creation of linkable, semantically rich open datasets. The work emphasizes the pivotal role of application profiles in fortifying the semantic interoperability of (meta)data, thereby elevating dataset openness.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"9 1","pages":"Article 100068"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140464109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data use policies on state COVID-19 dashboards in the United States: Key characteristics, topical focus, and identifiable gaps","authors":"Rong Tang,&nbsp;Zhan Hu,&nbsp;Yishan Zhang","doi":"10.1016/j.dim.2023.100050","DOIUrl":"10.1016/j.dim.2023.100050","url":null,"abstract":"<div><div>In this paper, we report the findings of an investigation into the data use policies published on the COVID-19 dashboards developed by the 50 state governments of the United States as well as the government of District of Columbia. Specifically, we examined the key attributes of the dashboard data notes, such as data source, update frequency, and data suppression disclaimers. We also studied the terms and phrases used, as well as topic themes of the data policy texts. Using a data policy analysis model, our results revealed a series of gaps and inconsistencies in the policy statements. Connecting these gaps and inconsistencies with potential problems that could violate individual Open Data Principles (ODP) and the FAIR principles, we made recommendations to help resolve these missing areas and fix the inconsistencies, so that open government data can be managed and used to further the very core of open data practice. Further research that we plan to carry out includes confirmation and validation of our analysis model and our approach of linking the examination and assessment of open data policy with ODP and the FAIR principles.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"9 1","pages":"Article 100050"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135200197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns in paradata preferences among the makers and reusers of archaeological data","authors":"Isto Huvila,&nbsp;Lisa Andersson,&nbsp;Olle Sköld","doi":"10.1016/j.dim.2024.100077","DOIUrl":"10.1016/j.dim.2024.100077","url":null,"abstract":"<div><div>Knowledge of data reusers' and makers' preferences of data that describe processes and practices (paradata) remains limited, especially concerning broader patterns of such priorities. The aim of this study is to address this gap. Drawing on an exploratory factor analysis of a survey of makers and users of archaeological data, the study investigates 1) what patterns related to types of informational content can be identified in data makers' and users’ views of the usefulness of specific types of paradata, 2) how the patterns differ between data makers and users, and 3) how the patterns can be explained in terms of information needs and preferences. The findings show that paradata preferences are patterned and there are differences between data-makers and data-users ideas of what is useful. However, the differences limit to details that make data related processes and practices understandable rather than to the broader patterns of what types of information is needed. We identified five broad categories of uses for paradata (Data collection procedures and tools, Data in context, Standards and guidelines, Credentials, Data processing), and corresponding, applicable types of paradata. The findings point also to indicative possibilities of linking paradata preferences to orientational, contextualising and content-oriented data practices. From a practical perspective, this study underlines the importance of approaching paradata not as a monolith but rather as an arrangement that is structured by different understandings of (para)data and how it is acted upon. Instead of caring for paradata in general, it is crucial to engage with specific types of paradata for different data practices. Keywords: paradata, archaeology, data management, data reuse, research data management.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 4","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-AI interaction research agenda: A user-centered perspective","authors":"Tingting Jiang ,&nbsp;Zhumo Sun ,&nbsp;Shiting Fu ,&nbsp;Yan Lv","doi":"10.1016/j.dim.2024.100078","DOIUrl":"10.1016/j.dim.2024.100078","url":null,"abstract":"<div><div>The rapid growth of artificial intelligence (AI) has given rise to the field of Human-AI Interaction (HAII). This study meticulously reviewed the research themes, theoretical foundations, and methodological frameworks of the HAII field, aiming to construct a comprehensive overview of this field and provide robust support for future investigations. HAII research themes include human-AI collaboration, competition, conflict, and symbiosis. Theories drawn from communication, psychology, and sociology support these studies, while the employed methods include both self-reporting and observational approaches commonly utilized in user studies. It is suggested that future research should broaden its focus to encompass diverse user groups, AI roles, and tasks. Moreover, it is necessary to develop multi-disciplinary theories and integrate multi-level research methods to support the sustained development of the field. This study not only furnishes indispensable theoretical and practical insights for forthcoming research endeavors but also catalyzes the realization of a future distinguished by seamless interaction between humans and AI.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 4","pages":"Article 100078"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141691159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact factor does not predict long-term article impact across 15 journals","authors":"Bjarne Bartlett ,&nbsp;Carter M. Zamora ,&nbsp;Jon-Paul Bingham ,&nbsp;Amy S Ebesu Hubbard ,&nbsp;Michelle Tseng ,&nbsp;Bryan Runck ,&nbsp;Michael Kantar","doi":"10.1016/j.dim.2024.100079","DOIUrl":"10.1016/j.dim.2024.100079","url":null,"abstract":"<div><div>Academic journals are ranked using a variety of methods with the most common metric being ‘journal impact factor’. Authors who publish in journals with higher impact factors are deemed to contribute more to their discipline. However, the impact factor of a journal does not indicate how long a specific article stays in the scientific discourse, and metrics that measure the length of time articles within a journal continue to be cited are not typically used. We examined citations of 443,732 research articles [786,064 total] between 1980 and 2020 across 15 journals. We explored the range of longevity values found across different journals as well as the relationship between impact factor and longevity. We found no relationship between impact factor and longevity, indicating that immediate attention to an article is not correlated with longer-term impact. In the set of journals that we examined, articles published in some journals (e.g., Ecology, Genetics) continued to be cited at a steady rate long beyond their initial publication date. This slow but steady citation accumulation resulted in the total citations in these journals approaching those of higher impact journals (e.g., Science, Nature) within the length of a typical academic career (30–40 years).</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 4","pages":"Article 100079"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How readers attentive and inattentive to task-related information scan: An eye-tracking study","authors":"Jing Chen ,&nbsp;Lu Zhang ,&nbsp;Quan Lu","doi":"10.1016/j.dim.2024.100073","DOIUrl":"10.1016/j.dim.2024.100073","url":null,"abstract":"<div><h3>Purpose</h3><div>Attentive to task-related information should be the highest priority for all readers engaged in task-reading. Investigating the scanning behaviors of attentive versus inattentive readers shed new insights into the sequential cognitive processes, but it has seldom been studied. This study investigates their global patterns on a global scale, pertaining to the whole length of scanpaths, and further compares local tactics, local strategies, and local strategy transitions on a local scale, related to the isolated regions of scanpath.</div></div><div><h3>Design/methodology/approach</h3><div>A regular style reading system with the question, navigating, and text areas on its interface, and two types of task, namely fact-finding (FF) and content understanding (CU), were designed in an eye-tracking experiment. 24 participants were placed into attentive (AR) or inattentive (IAR) readers groups according to their fixation duration on task-related paragraphs. A global sequence analysis algorithm, Needleman-Wunsch, was applied to uncover global patterns across the whole length of scanpaths (whole-scanpaths). A local sequence analysis method related to frequent sub-scanpaths was adopted to extract local tactics specific to the reader and task. Coding was performed to identify local strategies by classifying local tactics. A local strategy transition was further identified as a sequence of frequent local strategies at the beginning, middle, and ending phases.</div></div><div><h3>Findings</h3><div>Whole<strong>-</strong>scanpaths of AR significantly differed from those of IAR, despite the absence of global patterns for each group. Five types of local strategy were identified, namely <em>locating information</em> <em>(</em><em>LI</em><em>)</em>, <em>evaluating and verifying text relevance (EVR)</em>, <em>navigation heuristics (NH)</em>, <em>synthesizing information</em> <em>(</em><em>SI</em><em>)</em>, and <em>contextual clues (CC)</em>. AR applied all types in both tasks, whereas IAR applied only two types and stuck with <em>EVR</em>. Furthermore, two types of local strategy transition were identified: <em>comprehensive exploration</em> and <em>iterative content evaluation</em>. AR employed the former with the linear feature in FF and the spiral feature in CU, while IAR employed the latter in both tasks.</div></div><div><h3>Originality</h3><div>This study advances the knowledge of dynamic cognitive processing from an attentive and inattentive to task-related information perspective. An objective analysis perspective for obtaining global patterns, local tactics, local strategies, and local strategy transitions is provided, then it can provide new insights into automatically classifying readers. The results also generate detailed and valuable guidance for improving reading system design and training readers.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 4","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical insights into the interaction effects of groups at high risk of depression on online social platforms with NLP-based sentiment analysis","authors":"Yi Xiao ,&nbsp;Yutong Yang ,&nbsp;Haozhe Xu ,&nbsp;Shijuan Li","doi":"10.1016/j.dim.2024.100080","DOIUrl":"10.1016/j.dim.2024.100080","url":null,"abstract":"<div><div>With the proliferation of digital technology and the increasing prevalence of social media, some users at high risk of depression have opted to seek solace, acceptance, and assistance in online communities. However, the extant research is deficient in terms of the segmentation of groups, particularly subcultural groups. By analyzing the “Super Hashtags” and “Tree Hole” groups on Sina Weibo from January to March 2023 using a crawler and the ERNIE 3.0-Base model for sentiment analysis, the study uncovers distinct sentiment profiles and interaction patterns, revealing significant correlations between interaction metrics and sentiment levels. The findings indicate that while there are no significant differences in sentiment levels between the two communities, the “Tree Hole” community exhibits greater sentiment variability. Moreover, the study identifies that interaction behaviors are closely linked to sentiment states, emphasizing the importance of understanding the complex dynamics between online interactions and mental well-being. These insights contribute to the development of more effective support mechanisms within online platforms for individuals at risk of depression.</div></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"8 4","pages":"Article 100080"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}