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Abstract Native American faculty in science, technology, engineering, and mathematics (NAF‐STEM) disciplines are historically underrepresented. Creating inclusive academia for Indigenous people that typically live and thrive in rural communities requires insights into their personal, relational, and collective experiences. This study was guided by the Six Rs: relationship, respect, responsibility, relevance, representation, and reciprocity, and was informed by Indigenous Research Methodologies. Twelve NAF‐STEM from tribal colleges and non‐tribal institutions were asked to share their perspectives and experiences in seven Research Circles. NAF‐STEM joined sequential hybrid workshops over seven weeks on how to conduct qualitative data analysis. Authors conducted analysis on the transcripts of Research Circles for themes associated with the professional satisfaction and success of NAF‐STEM. Results of the study identified the importance of holistic support systems that remain mindful of both the opportunities and challenges facing NAF‐STEM and emphasize the significance of balancing the need for respectful relationships, adequate representation, shared responsibility, relevance of diversity, and reciprocity in STEM. Through implementation of the Six Rs throughout the research process, the study identified successes, support systems, and challenges of NAF‐STEM at both tribal and non‐tribal colleges and universities. These outcomes can inform institutions to create an equitable and inclusive environment for NAF‐STEM. 

Faculty members in science, technology, engineering, and mathematics (STEM) disciplines are typically expected to pursue grant funding and publish to support their research or teaching agendas. Providing effective professional development programs on grant preparation and management and on research publications is crucial. This study shares the design and implementation of such a program for Native STEM faculty (NAF-STEM) from two tribal colleges and one public, non-tribal, Ph.D. granting institution during a 3-year period. The overall development and implementation of the program is centered on the six R’s Indigenous framework – Respect, Relationship, Representation, Relevance, Responsibility, and Reciprocity. The role of NAF-STEM and their interactions with the program, as members of the community formed by their participation, impacted the program. Their practices and the program co-emerged over time, each providing structure and meaning for the other. Through such reciprocity, NAF-STEM and the program research team continually refined the program through their mutual engagement. They took on the shared responsibility of the program while they participated in and shaped its practices. The process and results of formative and summative assessment and the impact of COVID-19 on the program are reported. Results of the program offer lessons on the implementation of six R’s framework in professional development at institutions of higher education. 

Abstract Background Mass spectrometry (MS) uses mass-to-charge ratios of measured particles to decode the identities and quantities of molecules in a sample. Interpretation of raw MS depends upon data processing algorithms that render it human-interpretable. Quantitative MS workflows are complex experimental chains and it is crucial to know the performance and bias of each data processing method as they impact accuracy, coverage, and statistical significance of the result. Creation of the ground truth necessary for quantitatively evaluating MS1-aware algorithms is difficult and tedious task, and better software for creating such datasets would facilitate more extensive evaluation and improvement of MS data processing algorithms. Results We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating MS1 ground truth. The software retains the first version’s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving, and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also be used to view and explore the results of feature finding algorithms. Conclusions JS-MS 2.0 enables faster creation and inspection of MS1 ground truth data. It is publicly available with an MIT license at github.com/optimusmoose/jsms.