IU Indianapolis ScholarWorks :: Browsing by Author "Murillo, Angela P."

Browsing by Author "Murillo, Angela P."

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Application of Edge-to-Cloud Methods Toward Deep Learning
(IEEE, 2022-10) Choudhary, Khushi; Nersisyan, Nona; Lin, Edward; Chandrasekaran, Shobana; Mayani, Rajiv; Pottier, Loic; Murillo, Angela P.; Virdone, Nicole K.; Kee, Kerk; Deelman, Ewa; Library and Information Science, School of Computing and Informatics
Scientific workflows are important in modern computational science and are a convenient way to represent complex computations, which are often geographically distributed among several computers. In many scientific domains, scientists use sensors (e.g., edge devices) to gather data such as CO2 level or temperature, that are usually sent to a central processing facility (e.g., a cloud). However, these edge devices are often not powerful enough to perform basic computations or machine learning inference computations and thus applications need the power of cloud platforms to generate scientific results. This work explores the execution and deployment of a complex workflow on an edge-to-cloud architecture in a use case of the detection and classification of plankton. In the original application, images were captured by cameras attached to buoys floating in Lake Greifensee (Switzerland). We developed a workflow based on that application. The workflow aims to pre-process images locally on the edge devices (i.e., buoys) then transfer data from each edge device to a cloud platform. Here, we developed a Pegasus workflow that runs using HTCondor and leveraged the Chameleon cloud platform and its recent CHI@Edge feature to mimic such deployment and study its feasibility in terms of performance and deployment.
Blueprint: Cyberinfrastructure Center of Excellence
(Zenodo, 2021-03) Deelman, Ewa; Mandal, Anirban; Murillo, Angela P.; Nabrzyski, Jarek; Pascucci, Valerio; Ricci, Robert; Baldin, Ilya; Sons, Susan; Christopherson, Laura; Vardeman, Charles; Ferreira da Silva, Rafael; Wyngaard, Jane; Petruzza, Steve; Rynge, Mats; Vahi, Karan; Whitcup, Wendy R.; Drake, Josh; Scott, Erik; Library and Information Science, School of Informatics and Computing
In 2018, NSF funded an effort to pilot a Cyberinfrastructure Center of Excellence (CI CoE or Center) that would serve the cyberinfrastructure (CI) needs of the NSF Major Facilities (MFs) and large projects with advanced CI architectures. The goal of the CI CoE Pilot project (Pilot) effort was to develop a model and a blueprint for such a CoE by engaging with the MFs, understanding their CI needs, understanding the contributions the MFs are making to the CI community, and exploring opportunities for building a broader CI community. This document summarizes the results of community engagements conducted during the first two years of the project and describes the identified CI needs of the MFs. To better understand MFs' CI, the Pilot has developed and validated a model of the MF data lifecycle that follows the data generation and management within a facility and gained an understanding of how this model captures the fundamental stages that the facilities' data passes through from the scientific instruments to the principal investigators and their teams, to the broader collaborations and the public. The Pilot also aimed to understand what CI workforce development challenges the MFs face while designing, constructing, and operating their CI and what solutions they are exploring and adopting within their projects. Based on the needs of the MFs in the data lifecycle and workforce development areas, this document outlines a blueprint for a CI CoE that will learn about and share the CI solutions designed, developed, and/or adopted by the MFs, provide expertise to the largest NSF projects with advanced and complex CI architectures, and foster a community of CI practitioners and researchers.
Coming to America: Iranians' use of Telegram for immigration information seeking
(Emerald, 2020) Nikkhah, Sarah; Murillo, Angela P.; Young, Alyson Leigh; Miller, Andrew D.; Human-Centered Computing, School of Informatics and Computing
Purpose This study examines Iran-US migrants' use of the most popular messaging application in Iran—Telegram—and shows how they use it to manage their migration information practices. Design/methodology/approach This study took a qualitative observation approach. Over the course of six months, over 80 h of observations were conducted on Iran-US migration-related settings within Telegram. Findings This work identifies the information practices that emerge as users seek and share information related to Iran-US migration. Telegram plays a vital role across the immigration stages, predominantly in the pre-migration stage. This work also shows how the constraints and features of Telegram influence users' information sharing and seeking practices. Practical implications The findings support the implication that a social media platform that provides multiple ways to interact is likely to better support niche or unanticipated uses. Originality/value This study is the first of its kind to explore Iranian Immigrants information practices in the US. The immigration information practices observed during this study represent a valuable example of end-user appropriation within extraordinary constraints, which may be of use in other information-seeking contexts where dedicated or bespoke tools are impractical or ill-advised.
Confronting the Challenges of Computational and Social Perspectives of the Data Continuum
(Sciendo, 2020-06) Murillo, Angela P.; Curty, Renata G.; Jeng, Wei; He, Daqing; Library and Information Science, School of Informatics and Computing
As the availability of data is increasing everyday, the need to reflect on how to make these data meaningful and impactful becomes vital. Current data paradigms have provided data life cycles that often focus on data acumen and data stewardship approaches. In an effort to examine the convergence, tensions, and harmonies of these two approaches, a group of researchers participated in an interactive panel session at the Association of Information Science and Technology Annual meeting in 2019. The panel presenters described their various research activities in which they confront the challenges of the computational and social perspectives of the data continuum. This paper provides a summary of this interactive panel.
The Convergence of Computational and Social Approaches for Unveiling Meaningful and Valuable Data
(Wiley, 2019) Murillo, Angela P.; Curty, Renata G.; Jeng, Wei; He, Daqing; Library and Information Science, School of Informatics and Computing
The current data paradigm is seeking a more integrated and comprehensive framework to make sense of data and its derived issues. From the perspective of the data life cycle, we argue that computational and social approaches complement each other to confront data challenges. Computational approaches consist of ETL (extract, transform, and load), modeling, and machine learning techniques; social approaches include policy and regulations, data sharing and reuse behavior, reproducibility, ethical and privacy issues. In this panel, we frame these two approaches as data acumen and data stewardship. The merging of these two perspectives allows data not only to become discoverable, accessible, and interoperable, but also to further the value of revealing meaningful patterns and become supportive evidence for important decision making. In this panel, the opening facilitator and three panelists will report on their recent studies in terms of this convergence of both data acumen and stewardship while sharing their recent research insights on case studies in three disciplines: agriculture, biomedicine, and archeology.
Crafting an Innovative Model for Developing an Online Data Curriculum
(2021-09) Murillo, Angela P.
This poster presents the preliminary findings and observations of developing the undergraduate Applied Data and Information Science (ADIS) Bachelor of Science program. The ADIS program incorporates competencies and skillsets from Library and Information Science and Data Science and is an interdisciplinary collaboration between an LIS Department and a Human-Centered Computing department. The LIS courses in this program are online asynchronous courses. This poster presents the preliminary findings and observations regarding program development, curriculum development, course development, and online course delivery to undergraduates. This poster will present the LIS and data science models and frameworks that were utilized to develop the program learning outcomes from the program development perspective. This poster will discuss the specific LIS and data science competencies embedded into the curriculum from the curriculum development perspective. This poster will present examples of how specific data skill sets and competencies are incorporated into the course from the course development perspective. Lastly, this course will discuss best practices for delivering hands-on data-related curriculum to undergraduates in an online environment from an online course delivery perspective. Although this poster focuses on undergraduate program development, similar models can be used for the creation of masters-level data-related program development, as well as the lessons learned from the delivery of online asynchronous hands-on data-related courses. Strategic partnerships, data-related curriculum, and online course delivery are highly relevant for all levels of current and future LIS education and program development.
Data Curation Competencies, Skill sets, and Tools Analysis
(Springer, 2024) Murillo, Angela P.; Yoon, Angela; Duncan, Mitch; Thomas-Fennelly, Adam
The project aims to extend the current understanding of data curation competencies by examining existing skill sets and tools through a systematic analysis of data curation literature. For this research, the researchers reviewed forty-two data curation-related documents, including peer-reviewed literature, conference papers, and book sections through descriptive quantitative analysis and inductive qualitative content analysis based on a systematically created document protocol to extract informational items about the documents, as well as competencies, skills, and tools relevant to data curation activities. This paper presents the preliminary findings of this analysis and future steps for this project.
The Development of an Undergraduate Data Curriculum: A Model for Maximizing Curricular Partnerships and Opportunities
(Springer, 2018) Murillo, Angela P.; Jones, Kyle M. L.; Library and Information Science, School of Informatics and Computing
The article provides the motivations and foundations for creating an interdisciplinary program between a Library and Information Science department and a Human-Centered Computing department. The program focuses on data studies and data science concepts, issues, and skill sets. In the paper, we analyze trends in Library and Information Science curricula, the emergence of data-related Library and Information Science curricula, and interdisciplinary data-related curricula. Then, we describe the development of the undergraduate data curriculum and provide the institutional context; discuss collaboration and resource optimization; provide justifications and workforce alignment; and detail the minor, major, and graduate opportunities. Finally, we argue that the proposed program holds the potential to model interdisciplinary, holistic data-centered curriculum development by complimenting Library and Information Science traditions (e.g., information organization, access, and ethics) with scholarly work in data science, specifically data visualization and analytics. There is a significant opportunity for Library and Information Science to add value to data science and analytics curricula, and vice versa.
An examination of scientific data repositories, data reusability, and the incorporation of FAIR
(Whiley, 2020-10-22) Murillo, Angela P.
Scientific data repositories (SDRs) provide a way for scientists to share data through data deposition and reuse of deposited data. Over the last twenty-plus years, hundreds of scientific SDRs have become available. This research examines 132 SDRs. This study assesses if the information available in the SDRs aligned with what scientists need to determine data reusability and if the SDRs enforce FAIR principles.
Family Resiliance Technologies: Designing Collaborative Technologies for Caregiving Coordination in the Children's Hospital
(2023-03) Nikkhah, Sarah; Miller, Andrew D.; Bolchini, Davide; Martin-Hammond, Aqueasha M.; Murillo, Angela P.; Pratt, Wanda
Each year, the parents of approximately 15,300 kids will hear the words “Your child has cancer.” Families with hospitalized children must process a lot of stress and play a vital role in their child’s care. Hospitalized children need care and assistance processing medical information and going through their treatment. Therefore, their families must take on new responsibilities such as providing care, processing medical information, getting ready for the extensive and sometimes painful treatments, and facing the fear of losing their child. They must also adjust their daily duties, chores, and jobs to provide care to their hospitalized child. Previous research on families with hospitalized children shows that a lower level of stress and a higher level of communication among family members are significant predictors of long-term health outcomes after hospitalization. Social work and family therapy studies researched family resilience as these families’ ability to process and handle stress as a system. However, few technologies are designed to increase family resilience and support the family’s communication and collaboration when a child is hospitalized. My aim in this dissertation is to understand how collaborative technologies can help family members of hospitalized children (family caregivers) collaborate and coordinate with each other during the stressful extended hospitalization period. Through qualitative interviews and elicitation activities followed by iterative cycles of design, I showed that Family Resilience can be used as a lens to understand families’ collaborative processes and guide the design of collaborative technologies to support these families in adapting when they are under stress, and their usual routines as a family are constantly changing due to their child’s hospitalization. Therefore, there is an opportunity for HCI and CSCW to design collaborative technology that supports family resilience processes for families facing a crisis, such as having a hospitalized child with cancer.

Browsing by Author "Murillo, Angela P."

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