Angela P. Murillo

“I want your kidney!” Information seeking, sharing, and disclosure when soliciting a kidney donor online

OBJECTIVE This study investigates how people use the Internet to search for an altruistic kidney donor. Although many opinion pieces on this phenomenon have been written, this is the first qualitative study focused on online kidney solicitation from the potential recipients point of view. METHODS Eight participants - four who successfully found donors and four who were still searching - were interviewed, and inductive content analysis was performed. RESULTS Three themes appear in our data: choosing to go online to find a donor, information hubs, and information flow. These themes emphasize the process of information seeking and disclosure when using the Internet to find an altruistic kidney donor. CONCLUSION The benefits from searching online are not limited to the possibility of finding a kidney donor. Our participants also experience a wide variety of socially supportive activities from their online networks. Additionally, our participants felt that the potential benefits of finding a donor online outweighed risks to their privacy. PRACTICE IMPLICATIONS Not all potential recipients will find a kidney donor online. Participants indicated that through sharing educational information, staying positive, and actively maintaining their online solicitation efforts they received numerous social benefits even if they did not find a kidney donor.

Metadata Capital: Automating Metadata Workflows in the NIEHS Viral Vector Core Laboratory

This paper presents research examining metadata capital in the context of the Viral Vector Core Laboratory at the National Institute of Environmental Health Sciences (NIEHS). Methods include collaborative workflow modeling and a metadata analysis. Models of the laboratory’s workflow and metadata activity are generated to identify potential opportunities for defining microservices that may be supported by iRODS rules. Generic iRODS rules are also shared along with images of the iRODS prototype. The discussion includes an exploration of a modified capital sigma equation to understand metadata as an asset. The work aims to raise awareness of metadata as an asset and to incentivize investment in metadata R&D.

Examining data sharing and data reuse in the dataone environment

The Data Observation Network for Earth (DataONE), a U.S. NSF DataNet Partner, seeks to provide cyberinfrastructure for “open, persistent, robust, and secure access to…earth science observational data”. Scientists participating in DataONE are able to deposit, search, and reuse data available through various DataONE tools. The research presented in this poster-paper reports on two studies examining data sharing and reuse in the DataONE environment. The two studies include 1) a profiling data assessment that examines the data and metadata being deposited into the DataONE system for data sharing, and 2) a pilot think-aloud study that examines what factors influence decisions regarding data reuse. From the profiling data assessment, preliminary results indicate that data being deposited into the DataONE for sharing have three specific types of metadata available including a) dataset, b) access, and c) additional metadata. Results also indicated that there is variation regarding the robustness and completeness of information. Additionally, through the think-aloud study results indicated that particular aspects the metadata information was useful for decision-making regarding reuse of data for scientists, while other metadata aspects were described as not useful. The results section provide specific details of these findings and demonstrate how these two studies examine both data sharing and reuse within the DataONE environment.

How do scientists determine data reusability? A quasi-experiment think-aloud study: How do Scientists Determine Data Reusability? A Quasi-Experiment Think-Aloud Study

This poster presents preliminary findings of a quasi‐experiment think‐aloud study where scientists were presented four canned results of information regarding earth science data in a counter‐balanced design. Scientists were asked to think‐aloud regarding what information about the data assisted them in their ability to determine reusability of that dataset. Sixteen scientists from various earth science fields participated in the study. Each scientist responded to four canned results, a post‐result usefulness survey, a post‐search rank‐order survey, and a post‐search survey. Participants stated that concise data descriptions, attribute and unit lists, as well as research methods steps were particularly important in their ability to determine reusability of data. Participants preferred more robust results over less robust results, and stated that they would rather have too much information than to request the data to find out it actually did not serve their needs.

Metadata capital: Simulating the predictive value of Self-Generated Health Information (SGHI)

Metadata is crucial for understanding data, and can be viewed as a form of capital in the context of Big data. This paper reports on research simulating the potential of SGHI (Self-Generated Health Information) for predicting asthma episodes. A data set of 2,000 cases was generated using the Monte Carlo simulation method, with secondary modifications on air quality and geo-location. The research is being pursued as part of a National Consortium for Data Science (NCDS) effort. The research conducted demonstrates that metadata has an inherent “predictive value” and confirms that metadata is crucial for data analytics. The work presented also provides insights into the best direction for future work in this area.