Browsing by Author "Uzwyshyn, Raymond"
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Item The Application of Agile Project Management Principles for Library IT(International Federation of Library Associations and Institutions (IFLA), 2023-09-04) Uzwyshyn, RaymondThis research overviews pragmatic principles of Agile project management techniques for library IT projects and project teams in academic and research library environments. It is oriented towards implementing agile project management methods and tools in academic library IT projects ranging from creating technology-enhanced learning commons to digital library and archive creation to managing largescale digitization, creation of data repository infrastructures and digital media labs. The article overviews pragmatic online collaborative software tools (established and upcoming) and larger contextual principles of Agile methodologies within a wider project management field. The larger thesis contends that for the best success of Agile methods, these methods must be grounded in firmly established project management methodologies. This synergistic pairing leverages the best potential for progress within larger frameworks towards the highest chances of success for achieving desired project results on time, in scope and in budget. Principles, tools and methodologies are overviewed including scrums, sprints and kanban focusing on library IT and Agile project management, communication techniques and tools. The business case for an Agile Project Managers is reviewed. Speculation is then directed towards the future efficacy of Agile Project Management methodologies for increasingly complex 21st century projects and the larger AI paradigm shift currently occurring within society and library IT projects. Keywords: Agile Project Management, Library Project Management, Library Information Technology, Agile Methodologies, Agile PrinciplesItem Developing Technologically Enhanced Learning Spaces for New Millennia Academic Libraries(International Federation of Library Associations and Institutions (IFLA), 2023-07-26) Uzwyshyn, RaymondAs a third place of community and learning, university academic libraries are shifting from quiet study spaces for reflection and inspiration to spaces of creation, technology and interdisciplinarity. Information technologies, media technologies and learning technologies are rapidly expanding in academic libraries. Spaces such as digital media centers, digitization and 3D printing labs, and technology-centric digital literacy labs are now regular features in university libraries. Makerspaces and research data visualization walls have also become more common. These new types of integrated social and technology enhanced spaces enable new forms of literacy (digital, algorithmic, information-based) and learning for wider communities. This research overviews larger considerations and conceptual ideas towards envisioning and creating these types of spaces in our new millennia. It utilizes material from early-stage and completed projects to discuss conceptual synthetic ideas for development. Challenges of possibilities for integrating existing traditional library spaces in an existing structure with new spaces of technology will be discussed. Innovative antecedent and recent models of current technology enhanced learning commons including Texas State University Libraries (2014-2020), the University of West Florida (2011, Skylab), University of Miami Information Commons (2006) and early-stage projects (Mississippi State University, 2023) are referenced to reflect on new technology/architectural possibilities. Challenges towards reconfiguring the 19th century classroom grid towards 21st century learning technology possibilities are reflected upon. Pragmatic realities and visionary necessities of creative re-envisioning space possibilities will be emphasized to better create technologically enhanced libraries suitable for the 21st century. Keywords: academic libraries, architectural spaces, information technology, digital literacy, innovation.Item Online Data Research Repositories and Digital Scholarly Ecosystems: From Research Data and Datasets to Artificial Intelligence and Discovery(International Federation of Library Associations and Institutions (IFLA), 2022-07-06) Uzwyshyn, RaymondOnline networked data research repositories allow sharing and archiving of research data for open science and global research. This sharing opens data to modern interoperability and metadata for search, retrieval, and larger possibilities of open scholarly research ecosystems. Data research repositories are currently being leveraged to accelerate global research, promote international collaboration, and innovate on levels previously thought impossible. Research data repositories may also link data to further content from online publications and other digital communication and aggregation tools. This article pragmatically overviews such a data and content-centered ecosystem at Texas State University Libraries in the United States. The research then discusses the ecosystem's next level of planning and construction involving both bigger data possibilities for AI infrastructures\enabling researchers and their data towards Deep Learning (Neural Net) possibilities. The research uses examples of recent digitized medical image datasets for Cancer/melanoma detection through Deep Learning/Neural Net for global open science possibilities. These methodologies show large promise in making good use of online open data repositories, digital library ecosystems and online datasets. Recent AI research highlights the utility of several easily available online open-source digital library data repository and ecosystem components. An online data-centered research ecosystem accelerates open science, research and discovery on global levels. This open-source ecosystem and software infrastructure may be easily replicated by research institutions. Creating open online data infrastructures for research communities enables future global data and research, collaboration and the advancement of science, the academic research cycle on networked global levels.Item Steps Towards Building Library AI Infrastructures: Research Data Repositories, Scholarly Research Ecosystems and AI Scaffolding(International Federation of Library Associations and Institutions (IFLA), 2022-09-09) Uzwyshyn, RaymondArtificial Intelligence possibilities for Deep Learning, machine learning, neural nets and natural language processing present fascinating new AI library service areas. Most of these areas will be integrated into traditional academic library ‘information’ and ‘digital’ literacy programs and university research environments to enable research faculty, students and library staff. Most university faculty, graduate students and library staff working outside of Computer Science disciplines will require help to enable their data and research towards new AI possibilities. This research overviews methodologies and infrastructures for building new AI services within the ‘third interdisciplinary space’ of the academic library. A library is a very suitable space to enable these new ‘algorithmic literacy’ services. This work utilizes the pragmatic steps taken by Texas State University Libraries to set up good foundations. Data-centred steps for setting up digital scholarly research ecosystems are reviewed. Setting needed data-centred groundwork for library AI services enables research, data and media towards wider global online AI possibilities. Library AI external scholarly communications services are discussed as well as educational methodologies involving incremental steps for foundational AI scaffolding. Bootstrapping tools build on present systems and allow for the later enablement of future AI insights. Pathways are clarified from data collection to data cleaning, analytics and data visualization to AI applications. Focused steps needed are forwarded to move library staff, research faculty and graduate students towards these new AI possibilities. Data-centred ecosystems, retooling and building on present library staff expertise are reviewed. Data research repositories, algorithmic and programmatic literacy are recommended for later AI possibilities. Preliminary AI library working groups and R&D prototype methodologies for scaling up future library services and human resource infrastructures are considered. Recommended emergent pathways are prescribed to create library AI infrastructures to better prepare for a currently occurring global AI paradigm shift.