About this dataset

Context

The dataset presents the median household income across different racial categories in San Jose. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of San Jose population by race & ethnicity, the population is predominantly Asian. This particular racial category constitutes the majority, accounting for 38.58% of the total residents in San Jose. Notably, the median household income for Asian households is $179,214. Interestingly, Asian is both the largest group and the one with the highest median household income, which stands at $179,214.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Jose.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within San Jose. The dataset can be utilized to gain insights into gender-based income distribution within the San Jose population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within San Jose, among individuals aged 15 years and older with income, there were 369.55 thousand men and 327.21 thousand women in the workforce. Among them, 230,454 men were engaged in full-time, year-round employment, while 155,939 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 4.30% fell within the income range of under $24,999, while 6.36% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 50.68% of men in full-time roles earned incomes exceeding $100,000, while 38.04% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within San Jose. The dataset can be utilized to gain insights into gender-based income distribution within the San Jose population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within San Jose, among individuals aged 15 years and older with income, there were 225 men and 193 women in the workforce. Among them, 127 men were engaged in full-time, year-round employment, while 110 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 9.45% fell within the income range of under $24,999, while 17.27% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 10.24% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Jose median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in San Jose. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In San Jose, the median household income for the households where the householder is White increased by $36,516(33.54%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $108,887 in 2013 and $145,403 in 2023.
• Black or African American: In San Jose, the median household income for the households where the householder is Black or African American increased by $18,120(24.57%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $73,755 in 2013 and $91,875 in 2023.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Jose.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Jose median household income by race. You can refer the same here

We performed a temperature incubation experiment on board the RV Polarstern with a unicellular microbial community sampled from the Hausgarten station IV in Fram Strait during the campagin PS126 on June 1st, 2021 (Soltwedel et al., 2021). The community was sampled with CTD-bound niskin bottles (SBE 32 Carousel Water Sampler attached to a Seabird SBE911+ CTD-system; Seabird Scientific, Bellevue, WA, USA) from a depth of 15 m (Hoppmann et al., in review) and, after filtering the seawater through a 150 µm net, incubated in triplicate on plankton wheels in three temperature-controlled containers for ten days. To mimick todays and potential future temperature conditions of the Arctic ocean, we chose a control temperature of 2 °C, an intermediate warming scenario of 6 °C, and an extreme warming scenario of 9 °C. The goal was to investigate the effects of concurrent warming and Atlantification and therefore we chose an Arctic-Atlantic mixed water mass as community origin. This dataset comprises the chlorophyll, particulate nutrients, dissolved nutrients, carbonate chemistry, and flow cytometric measurements of the starting as well as the final communities. A total 300 mL of sample water for chlorophyll a, and 200 mL for particulate organic carbon and nitrogen (and the same volumes of ultrapure water for blank corrections), were vacuum-filtered (<−200 mbar) onto pre-combusted glass-fiber filters (GF/F Whatman, Maidstone, UK). These were put into 2 mL cryovials (Sarstedt, Nümbrecht, Germany) and kept at −80 °C until processing. Filters for chlorophyll a were manually shredded in 6 mL of 90% acetone and extracted for 20 h at 8 °C according to the EPA method 445.0 (Arar et al., 1997). The extract was centrifuged to remove residual filter snips, and Chlorophyll a was determined on a Trilogy fluorometer (Turner Designs, San Jose, CA, USA) after correcting for phaeopigments via acidification (1 M HCl). Filters for particulate nutrients were also acidified (0.5 M HCl) and dried for 12 h at 60 °C. Analysis was performed using a gas chromatograph CHNS-O elemental analyzer (EURO EA 3000, HEKAtech, Wegberg, Germany). pH was measured with a pH meter (EcoScan pH 5, ThermoFisher Scientific, Waltham, MA, USA) including a glass electrode (Sentix 62, Mettler Toledo, Columbus, OH, USA) that was one-point calibrated with a technical buffer solution (pH 7, Mettler Toledo, Columbus, OH, USA). Samples for total alkalinity and dissolved nutrients were filtered through a 0.22 µm cellulose-acetate syringe filter (Nalgene, Rochester, NY, USA) and stored at 4 °C in 125 mL borosilicate bottles and 15 mL polycarbonate tubes. Total alkalinity was measured by duplicate potentiometric titration using a TitroLine alphaplus autosampler (Schott Instruments, Mainz, Germany) and corrected with certified reference materials from A. Dickson (Scripps Institution of Oceanography, San Diego, CA, USA). The full carbonate system was calculated for tfin using the software CO2sys (Pierrot et al., 2011) with dissociation constants of carbonic acid by Mehrbach et al. (1973), refitted by Dickson and Millero (1987). Dissolved nutrients were measured colorimetrically at on a continuous-flow autoanalyzer (Evolution III, Alliance Instruments, Freilassing, Germany) following standard seawater analytical methods for nitrate and nitrite (Armstrong et al., 1967), phosphate (Eberlein et al., 1987), silicate (Grasshoff et al., 2009), and ammonium (Koroleff et al. 1970). For flow cytometric measurements, 3.5 mL of the sample were preserved with hexamine-buffered formalin (0.5% final concentration) and stored at −80 °C after dark incubation for 15 min. For analysis, samples were thawed at room temperature, vortexed, and measured at a fast speed for three minutes using an Accuri C6 flow cytometer (BD Sciences, Franklin Lakes, NJ, USA) after setting the threshold of the FL-3 channel to 900. Phenotypic diversity (D2) was calculated for each sample based on the flow cytometric fingerprint according to Props et al. (2016), using the values of FSC-H, SSC-H, FL-2, FL-3, and FL-4. Parts of the metadata as well as calculations from it were used in the publication of Ahme et al. (2023). All scripts can be found on GitHub (https://github.com/AntoniaAhme/PS126CommunityExperiment). The sequence data are available at the European Nucleotide Archive (ENA).

A dataset containing 24336 species occurrences available in GBIF matching the query: Geometry: POLYGON((-157.48535 61.19974,-169.6582 60.55818,-187.82227 54.05938,-189.94629 50.79205,-169.07227 49.87576,-155.36133 54.33361,-150.35156 52.05249,-86.60156 -54.02498,-77.28515 -55.84242,-66.95435 -56.49081,-67.21802 -55.14121,-71.89087 -52.2278,-72.1106 -51.61347,-73.17993 -51.29399,-73.31177 -50.20035,-72.85767 -48.15143,-73.38501 -46.96526,-72.25708 -44.39716,-72.75513 -44.15594,-71.97876 -41.30532,-73.35571 -40.67508,-72.96021 -39.4079,-73.07739 -37.63163,-71.23169 -33.42533,-71.34888 -30.65682,-71.01196 -30.06276,-71.05591 -29.06897,-70.41138 -27.02651,-70.16235 -24.61373,-69.6936 -21.40534,-70.07446 -17.97177,-74.67407 -15.12162,-75.65552 -13.54632,-79.40552 -6.68643,-80.43091 -6.01674,-80.76782 -4.83556,-79.0686 -2.81869,-80.0647 -1.82342,-79.22974 0.00732,-76.47583 3.93002,-76.81274 4.45595,-77.14966 7.09362,-77.41333 8.15349,-78.21899 8.89231,-79.39087 9.29731,-80.9436 8.55929,-81.8811 8.57378,-83.05298 8.93572,-86.12915 12.80466,-86.86157 12.71894,-86.94946 13.07591,-87.41821 13.91629,-88.28247 13.75984,-90.02563 14.17208,-92.12036 15.00846,-93.62915 16.48876,-94.72778 16.81155,-96.60644 17.22476,-103.52051 20.38582,-103.46191 22.51255,-110.55176 30.17046,-114.18457 33.45589,-119.92676 37.32358,-121.62598 42.79003,-118.22754 47.77379,-120.62988 51.0506,-128.59863 57.68849,-134.16504 60.39938,-142.36816 61.81466,-148.81348 63.11464,-157.48535 61.19974)) TaxonKey: Asteroidea HasGeospatialIssue: false. The dataset includes 24336 records from 87 constituent datasets: 2 records from Propuesta para rescatar y conservar la paleobiota de la Cantera Tlayúa, en Tepexí de Rodríguez, Puebla: Fase II. 7724 records from iNaturalist Research-grade Observations. 176 records from Inventario de corales pétreos, asteroideos, equinoideos y peces óseos de arrecifes de la costa de Jalisco, Colima y Michoacán. 4 records from Colección científica del Museo de Historia Natural Alfredo Dugés. 3 records from Biodiversidad de macroinvertebrados bénticos de la región marina Tijuana-Ensenada Baja California, México. 14 records from DMNS Marine Invertebrate Collection (Arctos). 12 records from Condon Fossil Collection. 10 records from Collection Echinodermata - ZMB. 1870 records from Royal BC Museum - Invertebrates Collection. 2 records from Bernice P. Bishop Museum. 1276 records from Geographically tagged INSDC sequences. 10 records from Succession of benthic hard-bottom communities abundance at station Errina2012_IS_solar2. 17 records from Inventario de la biota marina (cnidarios, poliquetos, moluscos, crustáceos, equinodermos y peces) del Santuario Islas e Islotes de Bahía Chamela, Jalisco, México. 663 records from Flora marina (Clorophyta, Phaeophyta, Rodophyta) y fauna conspicua (Echinodermata, Mollusca, Polychaeta) del Complejo Insular Espíritu Santo-Cerralvo-San José en BCS, México. 15 records from CHAS Malacology Collection (Arctos). 146 records from Base de datos de la Sala de Colecciones Biológicas de la Universidad Católica del Norte (SCBUCN). 3 records from Western Australian Museum provider for OZCAM. 2 records from Succession of benthic hard-bottom communities abundance at station Errina2012_AG. 32 records from Succession of benthic hard-bottom communities abundance at station Errina2012_IS_solar1. 92 records from COMARGIS: Information System on Continental Margin Ecosystems. 1 records from Macaulay Library Audio and Video Collection. 95 records from Centre for Biodiversity Genomics - Canadian Specimens. 3064 records from NMNH Extant Specimen Records. 1216 records from Catálogo de los equinodermos recientes de México (Fase II). 1 records from FBIP:IZIKO-UCT:Historical Invertebrates (1930-1980). 10 records from Abyssal fauna of the UK-1 polymetallic nodule exploration claim, Clarion-Clipperton Zone, central Pacific Ocean: Echinodermata. 1 records from Catalogue of the type specimens of sea stars (Asteroidea, Echinodermata) from research collections of the Zoological Institute, Russian Academy of Sciences. 5 records from Museums Victoria provider for OZCAM. 54 records from Inventario y monitoreo del Canal de Infiernillo para el comanejo de los recursos marinos en el territorio Seri, Golfo de California. 1 records from Questagame weekly feed. 1 records from Northern Territory Museum and Art Gallery provider for OZCAM. 14 records from Inventario de algas, corales pétreos, moluscos, crustáceos decápodos, equinodermos y peces de las islas de Revillagigedo, Colima, México. 2 records from University of Florida Invertebrate Paleontology. 26 records from Inventario de la biota terrestre (florístico) y marina (invertebrados, peces y macroalgas bentónicos) del parque nacional Isla Isabel. 3 records from RBINS DaRWIN. 1 records from IZIKO: Marine Invertebrate Collection (1900-2011). 31 records from Natural History Museum (London) Collection Specimens. 14 records from Marine Invertebrate from Argentina, Uruguay and Chile. 2 records from Colección de Zoología Invertebrados - Otros invertebrados. 27 records from Vulnerable marine ecosystems in the South Pacific Ocean region. 61 records from Equinodermos de la Colección de Referencia de Biología Marina de la Universidad del Valle (CRBMeq-UV). 1 records from UAM Earth Sciences Collection (Arctos). 42 records from Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" (MACN). Invertebrates National Collection (MACNIn). 156 records from Formación de una base de datos de la biodiversidad de fauna marina y costera en el Golfo de California. 348 records from UAM Invertebrate Collection (Arctos). 4 records from Biological observations from the Discovery Investigations 1925-1952. 8 records from Abyssal fauna of the UK-1 polymetallic nodule exploration claim, Clarion-Clipperton Zone, central Pacific Ocean: Echinodermata. 81 records from Australian Museum provider for OZCAM. 5 records from Invertebrate Paleontology Division, Yale Peabody Museum. 9 records from UWBM Invertebrate Paleontology Collection. 1 records from Arctic benthic invertebrate collection of the Zoological Institute of the Russian Academy of Science. 18 records from Paleobiology Database. 54 records from Canadian Museum of Nature General Invertebrate Collection. 1 records from Queensland Museum provider for OZCAM. 190 records from Inventario de corales pétreos, anélidos, crustáceos decápodos, moluscos, equinodermos y peces óseos de los arrecifes coralinos de Guerrero y Oaxaca. 7 records from The echinoderm collection (IE) of the Muséum national d'Histoire naturelle (MNHN - Paris). 3 records from Succession of benthic hard-bottom communities abundance at station Errina2012_MDD3. 122 records from Invertebrate Zoology Division, Yale Peabody Museum. 16 records from Deep-sea (> 1000 m) Goniasteridae (Valvatida; Asteroidea) from the North Pacific, including an overview of Sibogaster, Bathyceramaster n. gen. and three new species. 22 records from Megafauna of the UKSRL exploration contract area and eastern Clarion-Clipperton Zone in the Pacific Ocean: Echinodermata. 195 records from Museum of Comparative Zoology, Harvard University. 1 records from CMC Cincinnati Museum Center Invertebrate Paleontology. 96 records from International Barcode of Life project (iBOL). 2 records from Succession of benthic hard-bottom communities abundance at station Errina2012_IS_solar3. 1707 records from Gwaii Haanas Invertebrates (OBIS Canada). 2 records from Avistamientos de Biodiversidad Marina / Marine Biodiversity Sightings. 22 records from Megafauna of the UKSRL exploration contract area and eastern Clarion-Clipperton Zone in the Pacific Ocean: Echinodermata. 2668 records from CAS Invertebrate Zoology (IZ). 9 records from Lund Museum of Zoology (MZLU). 5 records from Coleção de Echinodermata do Museu Nacional - MNRJ-ECHINO. 1 records from Morfología funcional de mantos de rodolitos en el golfo de California, México. 1 records from Galathea II, Danish Deep Sea Expedition 1950-52. 78 records from Diveboard - Scuba diving citizen science observations. 15 records from Biodiversidad asociada a mantos de rodolitos y praderas de pastos marinos en Bahía Concepción, BCS. 2 records from NCSM Non-molluscan Invertebrates Collection. 6 records from naturgucker. 573 records from Echinoderms Collection - National Museum of Natural History, Chile. 143 records from UF Invertebrate Zoology. 434 records from NaGISA Project. 122 records from Field Museum of Natural History (Zoology) Invertebrate Collection. 15 records from Paleobiology Database. 316 records from Inventario de la fauna arrecifal asociada al ecosistema de Pocillopora en el Pacífico Tropical Mexicano. 4 records from Succession of benthic hard-bottom communities abundance at station Errina2012_MDD7. 14 records from Collection Echinodermata SMF. 76 records from sarce_rockyshores. 29 records from Diversity of the Indo-Pacific (DIPnet). 9 records from Succession of benthic hard-bottom communities abundance at station Errina2012_MDD4. Data from some individual datasets included in this download may be licensed under less restrictive terms.