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  • × year_i:[2020 TO 2030}
  1. Bullard, J.; Dierking, A.; Grundner, A.: Centring LGBT2QIA+ subjects in knowledge organization systems (2020) 0.03 
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    Abstract
    This paper contains a report of two interdependent knowledge organization (KO) projects for an LGBT2QIA+ library. The authors, in the context of volunteer library work for an independent library, redesigned the classification system and subject cataloguing guidelines to centre LGBT2QIA+ subjects. We discuss the priorities of creating and maintaining knowledge organization systems for a historically marginalized community and address the challenge that queer subjectivity poses to the goals of KO. The classification system features a focus on identity and physically reorganizes the library space in a way that accounts for the multiple and overlapping labels that constitute the currently articulated boundaries of this community. The subject heading system focuses on making visible topics and elements of identity made invisible by universal systems and by the newly implemented classification system. We discuss how this project may inform KO for other marginalized subjects, particularly through process and documentation that prioritizes transparency and the acceptance of an unfinished endpoint for queer KO.
    Date
    6.10.2020 21:22:33
  2. Rieder, B.: Engines of order : a mechanology of algorithmic techniques (2020) 0.02 
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    Abstract
    Software has become a key component of contemporary life and algorithmic techniques that rank, classify, or recommend anything that fits into digital form are everywhere. This book approaches the field of information ordering conceptually as well as historically. Building on the philosophy of Gilbert Simondon and the cultural techniques tradition, it first examines the constructive and cumulative character of software and shows how software-making constantly draws on large reservoirs of existing knowledge and techniques. It then reconstructs the historical trajectories of a series of algorithmic techniques that have indeed become the building blocks for contemporary practices of ordering. Developed in opposition to centuries of library tradition, coordinate indexing, text processing, machine learning, and network algorithms instantiate dynamic, perspectivist, and interested forms of arranging information, ideas, or people. Embedded in technical infrastructures and economic logics, these techniques have become engines of order that transform the spaces they act upon.
    Content
    Part I -- 1. Engines of Order -- 2. Rethinking Software -- 3. Software-Making and Algorithmic Techniques -- Part II -- 4. From Universal Classification to a Postcoordinated Universe -- 5. From Frequencies to Vectors -- 6. Interested Learning -- 7. Calculating Networks: From Sociometry to PageRank -- Conclusion: Toward Technical Culture Erscheint als Open Access bei De Gruyter.
    LCSH
    Algorithms ; Computer software
    Series
    Recursions: theories of media, materiality, and cultural techniques
    Subject
    Algorithms ; Computer software
  3. Du, C.; Cohoon, J.; Lopez, P.; Howison, J.: Softcite dataset : a dataset of software mentions in biomedical and economic research publications (2021) 0.02 
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    Abstract
    Software contributions to academic research are relatively invisible, especially to the formalized scholarly reputation system based on bibliometrics. In this article, we introduce a gold-standard dataset of software mentions from the manual annotation of 4,971 academic PDFs in biomedicine and economics. The dataset is intended to be used for automatic extraction of software mentions from PDF format research publications by supervised learning at scale. We provide a description of the dataset and an extended discussion of its creation process, including improved text conversion of academic PDFs. Finally, we reflect on our challenges and lessons learned during the dataset creation, in hope of encouraging more discussion about creating datasets for machine learning use.
    Form
    Software
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.7, S.870-884
  4. Yu, C.; Xue, H.; An, L.; Li, G.: ¬A lightweight semantic-enhanced interactive network for efficient short-text matching (2023) 0.02 
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    Abstract
    Knowledge-enhanced short-text matching has been a significant task attracting much attention in recent years. However, the existing approaches cannot effectively balance effect and efficiency. Effective models usually consist of complex network structures leading to slow inference speed and the difficulties of applications in actual practice. In addition, most knowledge-enhanced models try to link the mentions in the text to the entities of the knowledge graphs-the difficulties of entity linking decrease the generalizability among different datasets. To address these problems, we propose a lightweight Semantic-Enhanced Interactive Network (SEIN) model for efficient short-text matching. Unlike most current research, SEIN employs an unsupervised method to select WordNet's most appropriate paraphrase description as the external semantic knowledge. It focuses on integrating semantic information and interactive information of text while simplifying the structure of other modules. We conduct intensive experiments on four real-world datasets, that is, Quora, Twitter-URL, SciTail, and SICK-E. Compared with state-of-the-art methods, SEIN achieves the best performance on most datasets. The experimental results proved that introducing external knowledge could effectively improve the performance of the short-text matching models. The research sheds light on the role of lightweight models in leveraging external knowledge to improve the effect of short-text matching.
    Date
    22. 1.2023 19:05:27
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.2, S.283-300
  5. Acker, A.: Emulation practices for software preservation in libraries, archives, and museums (2021) 0.02 
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    Abstract
    Emulation practices are computational, technical processes that allow for one system to reproduce the functions and results of another. This article reports on findings from research following three small teams of information professionals as they implemented emulation practices into their digital preservation programs at a technology museum, a university research library, and a university research archive and technology lab. Results suggest that the distributed teams in this cohort of preservationists have developed different emulation practices for particular kinds of "emulation encounters" in supporting different types of access. I discuss the implications of these findings for digital preservation research and emulation initiatives providing access to software or software-dependent objects, showing how implications of these findings have significance for those developing software preservation workflows and building emulation capacities. These findings suggest that different emulation practices for preservation, research access, and exhibition undertaken in libraries, archives, and museums result in different forms of access to preserved software-accessing information and experiential access. In examining particular types of access, this research calls into question software emulation as a single, static preservation strategy for information institutions and challenges researchers to examine new forms of access and descriptive representation emerging from these digital preservation strategies.
    Form
    Software
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.9, S.1148-1160
  6. Aspray, W.; Aspray, P.: Does technology really outpace policy, and does it matter? : a primer for technical experts and others (2023) 0.02 
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    Abstract
    This paper reconsiders the outpacing argument, the belief that changes in law and other means of regulation cannot keep pace with recent changes in technology. We focus on information and communication technologies (ICTs) in and of themselves as well as applied in computer science, telecommunications, health, finance, and other applications, but our argument applies also in rapidly developing technological fields such as environmental science, materials science, and genetic engineering. First, we discuss why the outpacing argument is so closely associated with information and computing technologies. We then outline 12 arguments that support the outpacing argument, by pointing to some particular weaknesses of policy making, using the United States as the primary example. Then arguing in the opposite direction, we present 4 brief and 3 more extended criticisms of the outpacing thesis. The paper's final section responds to calls within the technical community for greater engagement of policy and ethical concerns and reviews the paper's major arguments. While the paper focuses on ICTs and policy making in the United States, our critique of the outpacing argument and our exploration of its complex character are of utility to actors in other political contexts and in other technical fields.
    Date
    22. 7.2023 13:28:28
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.8, S.885-904
  7. Luo, L.; Ju, J.; Li, Y.-F.; Haffari, G.; Xiong, B.; Pan, S.: ChatRule: mining logical rules with large language models for knowledge graph reasoning (2023) 0.02 
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    Abstract
    Logical rules are essential for uncovering the logical connections between relations, which could improve the reasoning performance and provide interpretable results on knowledge graphs (KGs). Although there have been many efforts to mine meaningful logical rules over KGs, existing methods suffer from the computationally intensive searches over the rule space and a lack of scalability for large-scale KGs. Besides, they often ignore the semantics of relations which is crucial for uncovering logical connections. Recently, large language models (LLMs) have shown impressive performance in the field of natural language processing and various applications, owing to their emergent ability and generalizability. In this paper, we propose a novel framework, ChatRule, unleashing the power of large language models for mining logical rules over knowledge graphs. Specifically, the framework is initiated with an LLM-based rule generator, leveraging both the semantic and structural information of KGs to prompt LLMs to generate logical rules. To refine the generated rules, a rule ranking module estimates the rule quality by incorporating facts from existing KGs. Last, a rule validator harnesses the reasoning ability of LLMs to validate the logical correctness of ranked rules through chain-of-thought reasoning. ChatRule is evaluated on four large-scale KGs, w.r.t. different rule quality metrics and downstream tasks, showing the effectiveness and scalability of our method.
    Date
    23.11.2023 19:07:22
  8. DuBose, J.: Cataloging virtual reality rrograms : making the future searchable (2024) 0.02 
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    Abstract
    While virtual reality (VR) programs are not new, only in recent years have libraries made these systems available for their patrons. Along with the VR systems, more and more programs are being released. These programs range from educational to entertainment. This paper discusses a project created at Mississippi State University Libraries to catalog their purchased VR programs and make them searchable to students and researchers via the OPAC.
    Form
    Software
  9. Das, S.; Naskar, D.; Roy, S.: Reorganizing educational institutional domain using faceted ontological principles (2022) 0.02 
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    Abstract
    The purpose of this work is to find out how different library classification systems and linguistic ontologies arrange a particular domain of interest and what are the limitations for information retrieval. We use knowledge representation techniques and languages for construction of a domain specific ontology. This ontology would help not only in problem solving, but it would demonstrate the ease with which complex queries can be handled using principles of domain ontology, thereby facilitating better information retrieval. Facet-based methodology has been used for ontology formalization for quite some time. Ontology formalization involves different steps such as, Identification of the terminology, Analysis, Synthesis, Standardization and Ordering. Firstly, for purposes of conceptualization OntoUML has been used which is a well-founded and established language for Ontology driven Conceptual Modelling. Phase transformation of "the same mode" has been subsequently obtained by OWL-DL using Protégé software. The final OWL ontology contains a total of around 232 axioms. These axioms comprise 148 logical axioms, 76 declaration axioms and 43 classes. These axioms glue together classes, properties and data types as well as a constraint. Such data clustering cannot be achieved through general use of simple classification schemes. Hence it has been observed and established that domain ontology using faceted principles provide better information retrieval with enhanced precision. This ontology should be seen not only as an alternative of the existing classification system but as a Knowledge Base (KB) system which can handle complex queries well, which is the ultimate purpose of any classification system or indexing system. In this paper, we try to understand how ontology-based information retrieval systems can prove its utility as a useful tool in the field of library science with a particular focus on the education domain.
  10. Bergman, O.; Israeli, T.; Whittaker, S.: Factors hindering shared files retrieval (2020) 0.02 
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    Abstract
    Purpose Personal information management (PIM) is an activity in which people store information items in order to retrieve them later. The purpose of this paper is to test and quantify the effect of factors related to collection size, file properties and workload on file retrieval success and efficiency. Design/methodology/approach In the study, 289 participants retrieved 1,557 of their shared files in a naturalistic setting. The study used specially developed software designed to collect shared files' names and present them as targets for the retrieval task. The dependent variables were retrieval success, retrieval time and misstep/s. Findings Various factors compromise shared files retrieval including: collection size (large number of files), file properties (multiple versions, size of team sharing the file, time since most recent retrieval and folder depth) and workload (daily e-mails sent and received). The authors discuss theoretical reasons for these negative effects and suggest possible ways to overcome them. Originality/value Retrieval is the main reason people manage personal information. It is essential for retrieval to be successful and efficient, as information cannot be used unless it can be re-accessed. Prior PIM research has assumed that factors related to collection size, file properties and workload affect file retrieval. However, this is the first study to systematically quantify the negative effects of these factors. As each of these factors is expected to be exacerbated in the future, this study is a necessary first step toward addressing these problems.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 72(2020) no.1, S.130-147
  11. Hartel, J.: ¬The red thread of information (2020) 0.02 
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    Abstract
    Purpose In The Invisible Substrate of Information Science, a landmark article about the discipline of information science, Marcia J. Bates wrote that ".we are always looking for the red thread of information in the social texture of people's lives" (1999a, p. 1048). To sharpen our understanding of information science and to elaborate Bates' idea, the work at hand answers the question: Just what does the red thread of information entail? Design/methodology/approach Through a close reading of Bates' oeuvre and by applying concepts from the reference literature of information science, nine composite entities that qualify as the red thread of information are identified, elaborated, and related to existing concepts in the information science literature. In the spirit of a scientist-poet (White, 1999), several playful metaphors related to the color red are employed. Findings Bates' red thread of information entails: terms, genres, literatures, classification systems, scholarly communication, information retrieval, information experience, information institutions, and information policy. This same constellation of phenomena can be found in resonant visions of information science, namely, domain analysis (Hjørland, 2002), ethnography of infrastructure (Star, 1999), and social epistemology (Shera, 1968). Research limitations/implications With the vital vermilion filament in clear view, newcomers can more easily engage the material, conceptual, and social machinery of information science, and specialists are reminded of what constitutes information science as a whole. Future researchers and scientist-poets may wish to supplement the nine composite entities with additional, emergent information phenomena. Originality/value Though the explication of information science that follows is relatively orthodox and time-bound, the paper offers an imaginative, accessible, yet technically precise way of understanding the field.
    Date
    30. 4.2020 21:03:22
    Source
    Journal of documentation. 76(2020) no.3, S.647-656
  12. Jha, A.: Why GPT-4 isn't all it's cracked up to be (2023) 0.02 
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    Abstract
    "I still don't know what to think about GPT-4, the new large language model (LLM) from OpenAI. On the one hand it is a remarkable product that easily passes the Turing test. If you ask it questions, via the ChatGPT interface, GPT-4 can easily produce fluid sentences largely indistinguishable from those a person might write. But on the other hand, amid the exceptional levels of hype and anticipation, it's hard to know where GPT-4 and other LLMs truly fit in the larger project of making machines intelligent.
    They might appear intelligent, but LLMs are nothing of the sort. They don't understand the meanings of the words they are using, nor the concepts expressed within the sentences they create. When asked how to bring a cow back to life, earlier versions of ChatGPT, for example, which ran on a souped-up version of GPT-3, would confidently provide a list of instructions. So-called hallucinations like this happen because language models have no concept of what a "cow" is or that "death" is a non-reversible state of being. LLMs do not have minds that can think about objects in the world and how they relate to each other. All they "know" is how likely it is that some sets of words will follow other sets of words, having calculated those probabilities from their training data. To make sense of all this, I spoke with Gary Marcus, an emeritus professor of psychology and neural science at New York University, for "Babbage", our science and technology podcast. Last year, as the world was transfixed by the sudden appearance of ChatGPT, he made some fascinating predictions about GPT-4.
    He doesn't dismiss the potential of LLMs to become useful assistants in all sorts of ways-Google and Microsoft have already announced that they will be integrating LLMs into their search and office productivity software. But he talked me through some of his criticisms of the technology's apparent capabilities. At the heart of Dr Marcus's thoughtful critique is an attempt to put LLMs into proper context. Deep learning, the underlying technology that makes LLMs work, is only one piece of the puzzle in the quest for machine intelligence. To reach the level of artificial general intelligence (AGI) that many tech companies strive for-i.e. machines that can plan, reason and solve problems in the way human brains can-they will need to deploy a suite of other AI techniques. These include, for example, the kind of "symbolic AI" that was popular before artificial neural networks and deep learning became all the rage.
    People use symbols to think about the world: if I say the words "cat", "house" or "aeroplane", you know instantly what I mean. Symbols can also be used to describe the way things are behaving (running, falling, flying) or they can represent how things should behave in relation to each other (a "+" means add the numbers before and after). Symbolic AI is a way to embed this human knowledge and reasoning into computer systems. Though the idea has been around for decades, it fell by the wayside a few years ago as deep learning-buoyed by the sudden easy availability of lots of training data and cheap computing power-became more fashionable. In the near future at least, there's no doubt people will find LLMs useful. But whether they represent a critical step on the path towards AGI, or rather just an intriguing detour, remains to be seen."
  13. Nikiforova, A.A.: ¬The systems approach (2022) 0.02 
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    Abstract
    The review attempts to compare different points of view on the essence of the systems approach, describe the terminological confusion around it and analyse the numerous definitions of system. It is shown that the vagueness and ambiguity of the concept of the systems approach is manifested in the use of a number of terms which are similar in meaning and close in sound to it. It is proposed to divide the existing definitions of system into descriptive and formal ones. The concepts included in the descriptive definitions, as well as the numerous synonymous terms denoting them, are divided into five conceptual-terminological groups that differ in their content and logical meaning. The meanings of such concepts as minimal constituent parts, emergence, environment, boundaries, purpose, functions of system and systems hierarchy are revealed. Some uses of the concept in knowledge organization are mentioned. The problem of systems classification is touched upon. Separate sections are devoted to the highlights of the history of the systems approach, its criticism and the significance. Particular attention is paid to criticism of the mathematization of the systems approach. Possible reasons for the decline in interest in the systems approach are identified. It is concluded that the systems approach helps to find new ways to solve scientific and practical problems.
  14. Butlin, P.; Long, R.; Elmoznino, E.; Bengio, Y.; Birch, J.; Constant, A.; Deane, G.; Fleming, S.M.; Frith, C.; Ji, X.; Kanai, R.; Klein, C.; Lindsay, G.; Michel, M.; Mudrik, L.; Peters, M.A.K.; Schwitzgebel, E.; Simon, J.; VanRullen, R.: Consciousness in artificial intelligence : insights from the science of consciousness (2023) 0.02 
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    Abstract
    Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive "indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.
  15. Moore, S.M.; Kiser, T.; Hodge, C.: Classification of print-based cartographic materials : a survey and analysis (2022) 0.02 
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    Abstract
    This paper examines the predominant systems used for the classification of print-based cartographic materials (primarily atlases and sheet maps). We present the results of a brief, widely distributed survey on the topic, followed by discussions of the distinctive characteristics of the classification systems used by survey respondents. The Library of Congress Classification and Dewey Decimal Classification systems were found to be widely used, with several other schemes also in use.
  16. Yang, X.; Li, X.; Hu, D.; Wang, H.J.: Differential impacts of social influence on initial and sustained participation in open source software projects (2021) 0.02 
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    Abstract
    Social networking tools and visible information about developer activities on open source software (OSS) development platforms can leverage developers' social influence to attract more participation from their peers. However, the differential impacts of such social influence on developers' initial and sustained participation behaviors were largely overlooked in previous research. We empirically studied the impacts of two social influence mechanisms-word-of-mouth (WOM) and observational learning (OL)-on these two types of participation, using data collected from a large OSS development platform called Open Hub. We found that action (OL) speaks louder than words (WOM) with regard to sustained participation. Moreover, project age positively moderates the impacts of social influence on both types of participation. For projects with a higher average workload, the impacts of OL are reduced on initial participation but are increased on sustained participation. Our study provides a better understanding of how social influence affects OSS developers' participation behaviors. It also offers important practical implications for designing software development platforms that can leverage social influence to attract more initial and sustained participation.
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.9, S.1133-1147
  17. Shahbazi, M.; Bunker, D.; Sorrell, T.C.: Communicating shared situational awareness in times of chaos : social media and the COVID-19 pandemic (2023) 0.02 
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    Abstract
    To effectively manage a crisis, most decisions made by governments, organizations, communities, and individuals are based on "shared situational awareness" (SSA) derived from multiple information sources. Developing SSA depends on the alignment of mental models, which "represent our shared version of truth and reality on which we can act." Social media has facilitated public sensemaking during a crisis; however, it has also encouraged mental model dissonance, resulting in the digital destruction of mental models and undermining adequate SSA. The study is concerned with the challenges of creating SSA during the COVID-19 pandemic in Australia. This paper documents a netnography of Australian public health agencies' Facebook communication, exploring the initial impact of COVID-19 on SSA creation. Chaos theory is used as a theoretical lens to examine information perception, meaning, and assumptions relating to SSA from pre to post-pandemic periods. Our study highlights how the initial COVID-19 "butterfly effect" swamped the public health communication channel, leaving little space for other important health issues. This research contributes to information systems, information science, and communications by illustrating how the emergence of a crisis impacts social media communication, the creation of SSA, and what this means for social media adoption for crisis communication purposes.
    Date
    22. 9.2023 16:02:26
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.10, S.1185-1202
  18. Bergman, M.K..: Hierarchy in knowledge systems (2022) 0.02 
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    Abstract
    Hierarchies abound to help us organize our world. A hierarchy places items into a general order, where more 'general' is also more 'abstract'. The etymology of hierarchy is grounded in notions of religious and social rank. This article, after a historical review, focuses on knowledge systems, an interloper of the term hierarchy since at least the 1800s. Hierarchies in knowledge systems include taxonomies, classification systems, or thesauri in information science, and systems for representing information and knowledge to computers, notably ontologies and knowledge representation languages. Hierarchies are the logical underpinning of inference and reasoning in these systems, as well as the scaffolding for classification and inheritance. Hierarchies in knowledge systems express subsumption relations that have flexible variants, which we can represent algorithmically, and thus computationally. This article dissects that variability, leading to a proposed typology of hierarchies useful to knowledge systems. The article argues through a perspective informed by Charles Peirce that natural hierarchies are real, can be logically determined, and are the appropriate basis for knowledge systems. Description logics and semantic language standards reflect this perspective, importantly through their open-world logic and vocabularies for generalized subsumption hierarchies. Recent research suggests possible mechanisms for the emergence of natural hierarchies.
    Series
    Reviews of concepts in knowledge organization
  19. Bedford, D.: Knowledge architectures : structures and semantics (2021) 0.02 
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    Abstract
    Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.
    Content
    Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together
    LCSH
    Information storage and retrieval systems / Management
    Subject
    Information storage and retrieval systems / Management
  20. Lee, D.J.; Stvilia, B.; Ha, S.; Hahn, D.: ¬The structure and priorities of researchers' scholarly profile maintenance activities : a case of institutional research information management system (2023) 0.02 
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    Abstract
    Research information management systems (RIMS) have become critical components of information technology infrastructure on university campuses. They are used not just for sharing and promoting faculty research, but also for conducting faculty evaluation and development, facilitating research collaborations, identifying mentors for student projects, and expert consultants for local businesses. This study is one of the first empirical investigations of the structure of researchers' scholarly profile maintenance activities in a nonmandatory institutional RIMS. By analyzing the RIMS's log data, we identified 11 tasks researchers performed when updating their profiles. These tasks were further grouped into three activities: (a) adding publication, (b) enhancing researcher identity, and (c) improving research discoverability. In addition, we found that junior researchers and female researchers were more engaged in maintaining their RIMS profiles than senior researchers and male researchers. The results provide insights for designing profile maintenance action templates for institutional RIMS that are tailored to researchers' characteristics and help enhance researchers' engagement in the curation of their research information. This also suggests that female and junior researchers can serve as early adopters of institutional RIMS.
    Date
    22. 1.2023 18:43:02
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.2, S.186-204

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