Caring for Data in Hawaiʻi Symposium 2023

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    Race/Ethnicity Categorization in Hawaiʻi
    ( 2023-04-14) Matsunaga, Masako
    Hawaiʻi is one of the most racially and ethnically diverse states in the US. Such a population profile often complicates race/ethnicity categorizations when data are prepared for analysis. The Hawaii population also includes a high proportion of mixed-race individuals. Categorization for those individuals is another challenge in data preparation. This presentation will discuss the challenge of working with data from racially/ethnically diverse communities and resources for categories and population size estimates for racial/ethnic groups, including the Biostatistics Core Hawai‘i Single-Race Categorization Tool.
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    Using an Open Source Python Toolbox (Signac) to Manage High Dimensional Research Data
    ( 2023-04-14) Xiyu Du, Chrisy
    Many research fields have entered the age of Big Data. For some researchers, big data means computationally generating large datasets with high dimensional parameter sweeps; for others, big data means generating terabytes of experimental data with many different types of metadata based on experimental conditions. Recording and storing these data in an organized way for future analysis can be challenging, as many ad hoc solutions might help the exact current situation but hurt one's progress later on. Having battled these challenges, I want to share my experience working with an open-source data management system based on Python called Signac. Signac was first developed in the Glotzer Group at the University of Michigan, where I was a graduate student, to help manage different kinds of molecular dynamics simulations, but later extended to support many different kinds of data. In this talk, I want to briefly talk about the design philosophies of Signac and give a quick demonstration of how one could use Signac to help with their research based on my personal experiences.
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    Kūlana Noiʻi: Indigenous Data Stewardship in Hawaiʻi
    ( 2023-04-14) Alegado, Rosie ; Hintzen, Katy ; Kahanamoku, Sara
    Each year, scientists conduct hundreds of research projects in Hawaiʻi that focus on the natural resources of the islands’ upland, coastal, and marine ecosystems, systems which are integral to the livelihoods, cultural practices, and religious traditions of Kanaka ʻŌiwi. Yet without guidance, this research too often leaves Kānaka out of research processes, including the decision-making and outcomes vital to determining the scope of a project and its long-term impact. The Kūlana Noiʻi (ethical research standards) were developed to meet the need for establishing reciprocal research partnerships in Hawaiʻi communities, reflecting researcher and community approaches and drawing from extensive partnershps between university scientists, kiaʻi, federal and state resource managers, and local nonprofits. To date, this process-oriented guidance has been used to train over 600 researchers, community member, and resource stewards. In recent updates to the guidance, feedback on the application of the Kūlana to community research scenarios has driven us towards developing a focus on data stewardship, and in particular, Indigenous Data Sovereignty. We will review the ways in which the Kūlana Noiʻi are applicable to developing collaborative relationships regarding the collection, use, and application of data relevant to Hawaiʻi. This processes includes guidance for ensuring that projects working with research data in Hawaiʻi meet Indigenous Data Soveiengity standards and meet their kuleana to ensure that communities have access to and ability to utilize data as well as decision-making power in determining how their information and data are shared.
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    A Call for Better Data: An Overview of Data Gaps Affecting People with Disabilities in Hawai'i
    ( 2023-04-14) Bond-Smith, Daniela
    Theoretically, data has the potential to bring about many benefits for marginalized people, especially people with disabilities (PwD). However, the control of and benefits from the tech and data revolution disproportionately excluded disabled and other marginalized groups. Andrejevic candidly summarizes that “the asymmetric relationship between those who collect, store, and mine large quantities of data, and those whom data collection targets” is a crucial source of “power imbalances in the digital era”. PwD are particularly likely to be on the “wrong” side of the digital divide, as life opportunities become linked to ability expectations regarding data production and consumption. “Data ableism” has been described by Charitsis and Lehtiniemi as “data (in)visibility [which] refers to the ability to produce data that render people visible to the system or conversely the ability to hide from it [… and] data (un)desirability relates to the ability to produce desired data that are deemed valuable”. In addition, owning, using and understanding data and tech have become necessary prerequisites for accessing many resources and services, often without considering appropriate accessibility features. There is a dearth of systematic efforts to collect data about the lives of PwD in Hawai'i and elsewhere. This leads to research agendas, services, and policy planning that overlook the needs of PwD. The most suitable existing data sources for studying disparities experienced by PwD are government-run survey data, but they have significant limitations, in particular in in terms of identifying PwD and measuring disability, and they lack sub-state geographical identifiers which are critical for teasing on differences in outcomes and access for PwD across the islands. Importantly, none of the existing data sources ask about PwD’s unmet needs, services gaps and accessibility of services and infrastructure. Based on these critical data gaps, we urgently need to advocate for more adequate data vis-à-vis government agencies and invest in research studies that conduct systematic, long-term, community-driven data collection about outcomes and experiences of PwD in Hawai'i. References: Andrejevic MB. The big data divide. International Journal of Communication. 8(1):1673–89. Charitsis V, Lehtiniemi T. Data Ableism: Ability Expectations and Marginalization in Automated Societies. Television & New Media. 2022 Feb 22;15274764221077660.
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    Hā Kūpuna National Resource Center for Native Hawaiian Elders: Decolonizing Research through Qualitative Methods and Community Partnership
    ( 2023-04-14) Kawakami, Keilyn Leina'ala ; Tanji, Tarin T. ; Kaitsuka, Kilohana ; Muneoka, Shelley ; Burrage, Rachel L. ; Gronowski, Chrisovolandou ; Keli'ipa'akaua, Justin Kepo'o ; Braun, Kathryn
    Housed under the Thompson School of Social Work & Public Health at the University of Hawai‘i at Mānoa, Hā Kūpuna National Resource Center for Native Hawaiian Elders, strives to decolonize Western research as we increase opportunities of Native Hawaiian elders to pass their knowledge and stories to younger generations. One of Hā Kūpuna’s current projects is a five-year qualitative study examining healthcare experiences among Native Hawaiian elders in rural communities to gain advice for medical and social service providers to improve Native Hawaiian health. The project was co-designed by ALU LIKE, Inc.’s Kumu Kahi program (Elderly Services Department), which advised us to conduct a series of three interviews with each elder to build rapport before jumping into questions about healthcare. The first interview focuses on establishing rapport and learning about the kupuna’s family and everyday life. The second interview asks about values they learned from their own kupuna, what they want to pass to their mo`opuna, and other strengths and resiliencies. The third interview hones in on healthcare experiences they had over their lifetime and what advice they would like to share with providers. Results from the first 26 kūpuna have revealed that many kūpuna grew up with limited access to allopathic healthcare (healthcare providers treating diseases and symptoms with drugs and surgery) and that families treated many illnesses and injuries with traditional Hawaiian cultural healing practices, including lāʻau lapaʻau (plant-based medicine), lomilomi (massage), and ho`oponopono (conflict resolution). Even with the increased access and utilization of allopathic medicine, many kūpuna preferred cultural practices or a combination of both. Kūpuna advised that allopathic healthcare providers should take the time to gain knowledge of Native Hawaiian history and culture, allow for use of both Hawaiian and allopathic modes of healing, and interact with patients on both a personal as well as a professional level. They also noted that increasing access to specialty care on Neighbor Islands could improve Native Hawaiian health and life expectancy. Results and experiences from the ALU LIKE interview project helped to inform the creation of a 48-page qualitative interviewing protocol aimed to help researchers avoid extractive practices by increasing their knowledge of Hawaiian history, engaging communities in research, and creating safe and trusting research environments. Although experiences of colonization and discrimination are unique to each Indigenous and minority group, this protocol can apply to other populations as they are at a similar risk for extractive research experiences as well. As elements of the protocols were developed, they were discussed in-depth with researchers, non-profit stakeholders, community-based organization leaders (including ALU LIKE, Inc.), and past research participants. The qualitative protocol includes sections summarizing the history of colonization and instances of poorly-executed research in Hawaiʻi that caused harm. Also included are examples of Native Hawaiian researchers who are changing the face of research, a guide for researcher self-reflection and cultural humility, roles for community members in research, data ownership and management, the need to give more than take from participants, and a step-by-step guide on how to successfully join with community partners to conduct one-on-one interviews. Included are tips on developing research questions, and gathering and reporting data in ways accessible to the community. This qualitative protocol can be used as a guide to decolonizing research. Hā Kūpuna is supported by the US Administration on Community Living (#90OIRC0001) and the Barbara Cox Anthony Endowment.
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    UHM Library’s Research Data Management and Sharing Course
    ( 2023-04-14) Young, Jonathan
    Research data management and sharing requirements have become increasingly important for research practice, and the UHM Library is dedicated to expanding its support in this area. This presentation will discuss the UHM Library initiative to increase support for the data needs of researchers. We will introduce the library's new online asynchronous course on data management and sharing, titled "Caring for Data." The talk will offer a succinct overview of the course structure, featuring four modules: Research Data Concepts, Working with Research Data, Data Sharing and Planning, and Data in Hawaiʻi. Graduate students and faculty are encouraged to explore how this open access online course can help researchers comply with data sharing mandates or enhance the quality of their research data management practices, and more generally to think of the UHM Library as a partner in their research data practices. Note: Development of the course is funded by the National Library of Medicine, National Institutes of Health, Department of Health and Human Services, under Cooperative Agreement Number UG4LM013725 with the University of Washington.
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    Parachute Science in Hawaiʻi: Assessing Local Connectivity of Hawaiʻi Based Marine and Coastal Research
    ( 2023-04-14) Hintzen, Katy ; Alegado, Rosie ; Kahanamoku, Sara
    As a site with some of the highest levels of tropical marine endemism on the planet, the Hawaiian Islands have attracted marine and coastal researchers for decades. Much of this research has been conducted by scientists from outside states or countries, typically with high financial and scientific resources, who travel to Hawaiʻi to collect data and produce results that ultimately fail to circulate back to the communities from which the data was collected. This model of reearch is commonly known as “parachute science” or “colonial science.” Studies of parachute science in other places around the globe show that Indigenous communities typically carry the burden of these extractive research models, while simultaneously stewarding a majority of the worldʻs biodiversity with innovative biocultural techniques. To begin to unravel the historical extent of parachute research in Hawaiʻi, we analyzed the percentage of Hawaiʻi-based versus externally-located authors on coastal and marine research publications using data from Hawaiʻi. While Hawaiʻi-based authorship does not solelly determine whether a project is contributing to extractive science, this pilot effort attempts to determine how research data in Hawaiʻi is utilized, and by whom. We find that while the total amount of research done in the Hawaiian islands has increased over the past 30 years, a majority of this increase derives from an increase in the number of externally-based publications. Hawaiʻi-based authorship has remained relatively constant—and low—over this time period. We will present on the implications of this finding for Hawaiʻi researchers, as well as future directions that explore the potential drivers of these research disparities.
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    Healthcare Database and Research at Biostatistics Core Facility of John A. Burns School of Medicine
    ( 2023-04-14) Ahn, Hyeong Jun ; Lim, Eunjung ; Roman, Meliza
    The Department of Quantitative Health Science at John A. Burns School of Medicine operates a Biostatistics Core Facility, which employs extensive healthcare databases to advance health-related research and enhance our understanding of healthcare. The Core Facility is dedicated to offering biostatistical research assistance to basic science, clinical, and translational researchers. Its expertise lies in the areas of study design, data management and analysis, grant proposal development, methodology research, and education in biostatistics and related fields.
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    Decolonizing Research & Data Through Feminist Methodologies
    ( 2023-04-14) Grillet, Patricia
    What kinds of questions we intend to answer when collecting and analyzing data? Are our questions inclusive enough? Feminism offers the means to start decolonizing data even before we gather it, by opening up the questions that we think are important, focusing on issues that have always been there, but have been overlooked by our society in the past for different reasons. Decolonizing research methods is about putting the lens on issues that have been found irrelevant, or perhaps have even been ignored as valuable knowledge coming from populations that have been traditionally neglected by scientific research, such as single mothers, disabled black people, poor immigrants, just to name a few. Feminism not only opens up the spectrum of issues to be researched, but also provides creative ways to collect data and to analyze it, proposing ways to reduce or eliminate unequal power relations among researchers and participants, construct fairer relationships and create better life experiences for all, fostering collaboration, honesty and opportunities (Dána-Ain Davis & Christa Craven, 2023).
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    Bots are getting smarter: Online survey data collection in the age of sophisticated AI
    ( 2023-04-14) Matheis, Maya ; Takahashi, Kiriko ; Richard, Sarah
    In early summer of 2022, our team launched an online survey using SurveyMonkey to collect data about teen health in Hawai’i for a needs assessment being conducted in collaboration with the Hawaii State Department of Health. The survey was for teens and youth with special health care needs, as well as their parents/caregivers, and aimed to collect data about needs and barriers to their healthcare. We offered an incentive of a $20 gift card for participation to reach a few hundred families within the state of Hawai’i. We used flyers with QR code and asked community partners to share via listservs and social media. Within 12 hours of sharing information with community partners, we had over 1500 survey responses. A quick look revealed that the vast majority of the responses were from bots– automated programs designed to complete online surveys offering monetary incentives. In fact, only about 50 responses of 1500 appeared to be submitted by actual humans. We quickly shut down the survey, regrouped, and did some research on survey bots, which very recently have become sophisticated enough to bypass CAPTCHA safeguards. In this presentation, we will share about our experiences in developing strategies to filter out bot responses from datasets, our audit of survey platforms and our new platform-of-choice (REDCap), pre-emptive strategies to build safeguards, and facilitate a discussion on the implications for online data collection.