Multiple subaerial landslides adjacent to Prince William Sound, Alaska (for example, Dai and others, 2020; Higman and others, 2023; Schaefer and others, 2024) pose a threat to the public because of their potential to generate ocean waves (Barnhart and others, 2021, 2022; Dai and others, 2020) that could affect towns and marine activities. One bedrock landslide on the west side of Barry Arm fjord drew international attention in 2020 because of its large size (~500M m3) and tsunamigenic potential (Dai and others, 2020). As part of the U.S. Geological Survey response to the detection of the potentially tsunamigenic landslide at Barry Arm, as well as a broader effort to evaluate bedrock landslide and tsunamigenic potential throughout Prince William Sound (for example, Schaefer and others, 2024), we continued rock mass quality assessments and collection of structural geology data in northwest and northcentral Prince William Sound in July, 2022 (see associated data from 2021 in Coe and others, 2024). The quality (strength) of a rock mass depends on the properties of intact rock and the characteristics of discontinuities (for example, bedding, fractures, cleavage) that cut the rock. Rock mass quality can be estimated in the field using a variety of classification schemes. In 2022, we accessed sites by boat, helicopter, and hiking. At each field site, we made our measurements at rock outcrops, which were typically found at the base of cliffs, along ridge lines, in flat areas in coastal zones, and in areas recently scoured and plucked by glaciers. In two dimensions, outcrops ranged in size from about 30 m2 to 100 m2. We visited a total of 49 sites in the field. Most sites were in metamorphosed Cretaceous flysch, but a few were in Tertiary granitic rocks (Nelson and others, 1985; Wilson and others, 2015; Winkler, 1992). Of the 49 sites, we collected rock mass quality data and structural data at 39 sites (site names beginning in “rmc”), and only sparse structural data at 10 sites (site names beginning in “srl”). At the 39 full sites, we collected data that were later used to classify rock mass quality according to four commonly used classification schemes: (1) Rock Mass Quality (Q, for example, Barton and others, 1974; Coe and others, 2005) (2) Rock Mass Rating (RMR, for example, Bieniawski, 1989) (3) Slope Mass Rating (SMR, for example, Moore and others, 2009; Romana, 1995) (4) Geologic Strength Index (GSI, for example, P. Marinos and Hoek, 2000; V. Marinos and others, 2005) We also determined Rock Quality Designation (RQD, for example, Deere and Deere, 1989; Palmström, 1982) and estimated intact rock strength using a Proceq Rock Schmidt Type L Hammer (see RatingsReadMe.pdf for details). Schmidt Hammer rebound values were converted to Uniaxial Compressive Strength (UCS) using equations developed for the same rock types that we observed in the field, but at different locations. For flysch, rebound values from the Type L Schmidt Hammer were converted to UCS by the equation shown in Table 3 and Figure 3 of Morales and others (2004). For granitic rocks, rebound values from the Type L Schmidt Hammer were converted to UCS by the equation shown in Figure 3 of Aydin and Basu (2005). Additionally, we collected strikes and dips of any observed bedding, fractures, and cleavage. All four rock mass quality classification schemes use data from characteristics of discontinuities present in the rock. Discontinuity data that we collected in the field included: total number of discontinuities, roughness of the surface of the discontinuities, number of sets of discontinuities, type of filling or alteration on the surface of discontinuities, aperture or “openness” of discontinuities, and the amount of water present. Numerical ratings for each of these factors are assigned based on the correlation of field measurements and observations with descriptive rankings. The rankings and any additional details used for Q, RMR, SMR, and GSI classification schemes are shown in Tables 1-3 and Figures 1-2 in the RatingsReadMe.pdf. A file of a blank field data collection sheet is also included in the RatingsReadMe.pdf. Samples of rock were collected at some sites. These sample names are noted in a column in the RMQMeasurements_Rating_Values2022.csv. Physical samples are held at the Geologic Hazards Science Center in Golden, Colorado. This data release includes: (1) a spreadsheet of all field measurements, numerical ranking values, and calculated Q, RMR, SMR, GSI, and RQD values (RMQMeasurements_Ratings_Values2022.csv), (2) a spreadsheet of all structural measurements (StructuralData2022.csv), (3) a spreadsheet of the planar and toppling calculations used for determining SMR values (SMRCalculationsWorksheet.csv), (4) a spreadsheet with the final Q, RMR, SMR, GSI, Uniaxial Compressive Strength (UCS), and RQD values for each site (FinalRockStrength_QualityValues2022.csv), (5) photos from each site and any relevant sketches (PhotosBySite2022.zip), (6) Google Earth file of 2022 site locations (SiteLocations2022.kml), (7) a summary file with extra information about data collection, processing, and each classification system (RatingsReadMe.pdf), (8) and a readme (README.txt). Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References: Aydin, A. and Basu, A., 2005, The Schmidt hammer in rock material characterization, Engineering Geology, p. 1–14, https://doi.org/doi:10.1016/j.enggeo.2005.06.006 Barnhart, K.R., Collins, A.L., Avdievitch, N.N., Jones, R.P., George, D.L., Coe, J.A., and Staley, D.M., 2022, Simulated inundation extent and depth in Harriman Fjord and Barry Arm, western Prince William Sound, Alaska, resulting from the hypothetical rapid motion of landslides into Barry Arm Fjord, Prince William Sound, Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/P9QGWH9Z Barnhart, K.R., Jones, R.P., George, D.L., Coe, J.A., and Staley, D.M., 2021, Preliminary Assessment of the Wave Generating Potential from Landslides at Barry Arm, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2021–1071, 28 p., https://doi.org/10.3133/ofr20211071 Barton, N., Lien, R., and Lunde, J., 1974, Engineering classification of rock masses for the design of tunnel support, Rock Mechanics, v. 6, p. 189–236, https://doi.org/10.1007/BF01239496 Bieniawski, Z. T., 1989, Engineering rock mass classifications a complete manual for engineers and geologist in mining, civil, and petroleum engineering, John Wiley & Sons., New York, 251 p. Coe, J. A., Belair, G. M., Avdievitch, N. N., Lahusen, S. R., Macias, M. A., Collins, B. D., and Staley, D. M., 2024, Rock mass quality and structural geology observations in northwest Prince William Sound, Alaska from the summer of 2021: U.S. Geological Survey data release, https://doi.org/10.5066/P9UBHS4Q Coe, J.A., Harp, E.L., Tarr, A.C., and Michael, J.A., 2005, Rock-Fall Hazard Assessment of Little Mill Campground, American Fork Canyon, Uinta National Forest, Utah: U.S. Geological Surve Open-File Report 2005–1229, 48 p., two 1:3000-scale plates, https://pubs.usgs.gov/of/2005/1229 Dai, C., Higman, B., Lynett, P.J., Jacquemart, M., Howat, I.M., Liljedahl, A.K., Dufresne, A., Freymueller, J.T., Geertsema, M., Ward Jones, M., Haeussler, P.J., 2020, Detection and Assessment of a Large and Potentially Tsunamigenic Periglacial Landslide in Barry Arm, Alaska, Geophysical Research Letters, v. 47 (22), https://doi.org/10.1029/2020GL089800 Deere, D.U., and Deere, D.W., 1989, Rock Quality Designation (RQD) after twenty years: Contract Report GL-89-1, U.S. Army Engineer Waterways Experiment Station, Vicksburg, Miss., 25 p. Higman, B., Lahusen, S.R., Belair, G.M., and Staley, D.M., 2023, Inventory of Large Slope Instabilities, Prince William Sound, Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/P9XGMHHP Marinos, P., and Hoek, E., 2000, GSI: a geologically friendly tool for rock mass strength estimation, In Proceedings of the GeoEng2000 at the international conference on geotechnical and geological engineering, Melbourne: Technomic publishers, Lancaster, p. 1422–1446 Marinos, V., Marinos, P., and Hoek, E., 2005, The geological strength index: applications and limitations, Bulletin of Engineering Geology and the Environment, v. 64(1), p. 55–65, https://doi.org/10.1007/s10064-004-0270-5 Moore, J.R., Sanders, J.W., Dietrich, W.E., and Glaser, S.D., 2009, Influence of rock mass strength on the erosion rate of alpine cliffs, Earth Surface Processes and Landforms, v. 34(10), p. 1339–1352, https://doi.org/10.1002/esp.1821 Morales, T., Uribe-Etxebarria, G., Uriarte, J. A., and Fernández De Valderrama, I., 2004, Geomechanical characterisation of rock masses in Alpine regions: The Basque Arc (Basque-Cantabrian basin, Northern Spain), Engineering Geology, 71(3–4), p. 343–362, https://doi.org/10.1016/S0013-7952(03)00160-1 Nelson, S.W., Dumoulin, J.A., and Miller, M.L., 1985, Geologic map of the Chugach National Forest: U.S. Geological Survey Miscellaneous Field Studies Map MF–1645–B, scale 1:250,000, https://doi.org/10.3133/mf1645B Palmström, A., 1982, The volumetric joint count—A useful and simple measure of the degree of jointing, Proceedings of the 4th Congress of the International Association of Engineering Geologists, New Delhi, India, p. 221–228. Romana, M., 1995, The geomechanical classification SMR for slope correction: Proceedings of the Eighth International Congress on Rock Mechanics, Tokyo, Japan, p. 1085–1092. Schaefer, L.N., Kim, J., Staley, D.M., Lu, Z., and Barnhart, K.R., 2024, Satellite interferometry landslide detection and preliminary tsunamigenic plausibility assessment in Prince William Sound, southcentral Alaska: U.S. Geological Survey Open-File Report 2023–1099, 22, https://doi.org/10.3133/ofr20231099 Wilson, F.H., Hults, C., Mull, C.G., and Karl, S.M., 2015, Geologic map of Alaska: U.S. Geological Survey Scientific Investigations Map 3340, pamphlet 196 p., 2 sheets, scale 1:1,584,000, https://doi.org/10.3133/sim3340 Winkler, G.R., 1992, Geologic map and summary geochronology of the Anchorage 1 degrees x 3 degrees quadrangle, southern Alaska: U.S. Geological Survey Miscellaneous Investigations Series Map I–2283, 1 sheet, scale 1:250,000, https://doi.org/10.3133/i2283