Gold rose to 3,868.31 USD/t.oz on October 1, 2025, up 0.24% from the previous day. Over the past month, Gold's price has risen 9.44%, and is up 45.41% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on October of 2025.

Dataset of historical annual gold prices from 1970 to 2024, including significant events and acts that impacted gold prices.

Silver rose to 47.40 USD/t.oz on October 3, 2025, up 0.87% from the previous day. Over the past month, Silver's price has risen 16.54%, and is up 47.27% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on October of 2025.

Gold Reserves in China increased to 2298.53 Tonnes in the second quarter of 2025 from 2292.31 Tonnes in the first quarter of 2025. This dataset provides - China Gold Reserves - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Rhodium traded flat at 7,100 USD/t oz. on October 2, 2025. Over the past month, Rhodium's price has fallen 2.74%, but it is still 50.26% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Rhodium - values, historical data, forecasts and news - updated on October of 2025.

Bullion Price: Monthly Average: Mumbai: Gold: Standard data was reported at 84,995.000 INR/10 g in Feb 2025. This records an increase from the previous number of 79,079.000 INR/10 g for Jan 2025. Bullion Price: Monthly Average: Mumbai: Gold: Standard data is updated monthly, averaging 9,691.000 INR/10 g from Apr 1990 (Median) to Feb 2025, with 419 observations. The data reached an all-time high of 84,995.000 INR/10 g in Feb 2025 and a record low of 3,285.000 INR/10 g in Jul 1990. Bullion Price: Monthly Average: Mumbai: Gold: Standard data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.PG002: Memo Items: Bullion Price.

The dataset contains year- and month-wise compiled data on the average prices of Gold (Standard) and Silver at Mumbai in India

About this dataset

Context

The dataset tabulates the Gold Bar population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Gold Bar. The dataset can be utilized to understand the population distribution of Gold Bar by age. For example, using this dataset, we can identify the largest age group in Gold Bar.

Key observations

The largest age group in Gold Bar, WA was for the group of age 50 to 54 years years with a population of 201 (8.60%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Gold Bar, WA was the 85 years and over years with a population of 5 (0.21%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Gold Bar is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Gold Bar total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gold Bar Population by Age. You can refer the same here

This document contains statistical data and analysis of global gold demand and prices from 2010 to 2024, presented by Dojipedia, a website focused on Forex investment information. The data is organized quarterly and includes various categories of gold demand such as jewelry fabrication, technology use, investment, and central bank purchases. It also provides the LBMA gold price in US dollars per ounce for each quarter.The document highlights significant events that influenced gold prices and demand during this period. These events include major economic crises, geopolitical tensions, and market shifts. For instance, it mentions the European debt crisis in 2010, the U.S. credit rating downgrade in 2011, the Federal Reserve's quantitative easing tapering signals in 2013, and the COVID-19 pandemic's impact starting in 2020.The data shows how gold demand and prices often increase during times of economic uncertainty or political instability, as investors view gold as a safe-haven asset. For example, gold prices reached record highs in 2024 amid global economic and geopolitical uncertainties.Dojipedia presents itself as a platform with five years of Forex market investment experience. The site offers free educational content on technical analysis methods such as Elliott Wave, ICT Trading, and Smart Money Concept. It also mentions plans to publish free books on technical analysis.The document includes a disclaimer stating that the information provided is for general purposes only and not financial advice. It warns about the high risks associated with investing in financial markets like CFDs, Forex, cryptocurrencies, and gold. The disclaimer emphasizes that leveraged products may not be suitable for all investors due to the high risk to capital.Overall, this document serves as a comprehensive resource for those interested in gold market trends and their relationship to global economic events over the past decade and a half.

About this dataset

Context

The dataset tabulates the Gold Hill population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Gold Hill. The dataset can be utilized to understand the population distribution of Gold Hill by age. For example, using this dataset, we can identify the largest age group in Gold Hill.

Key observations

The largest age group in Gold Hill, OR was for the group of age 35 to 39 years years with a population of 140 (11.10%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Gold Hill, OR was the 85 years and over years with a population of 8 (0.63%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Gold Hill is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Gold Hill total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gold Hill Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Gold Beach population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Gold Beach. The dataset can be utilized to understand the population distribution of Gold Beach by age. For example, using this dataset, we can identify the largest age group in Gold Beach.

Key observations

The largest age group in Gold Beach, OR was for the group of age 65 to 69 years years with a population of 283 (11.17%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Gold Beach, OR was the 80 to 84 years years with a population of 32 (1.26%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Gold Beach is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Gold Beach total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gold Beach Population by Age. You can refer the same here

Gold Reserves in the United States remained unchanged at 8133.46 Tonnes in the second quarter of 2025 from 8133.46 Tonnes in the first quarter of 2025. This dataset provides - United States Gold Reserves - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the population of Gold Hill by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Gold Hill. The dataset can be utilized to understand the population distribution of Gold Hill by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Gold Hill. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Gold Hill.

Key observations

Largest age group (population): Male # 35-39 years (68) | Female # 10-14 years (78). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Gold Hill population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Gold Hill is shown in the following column.
• Population (Female): The female population in the Gold Hill is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Gold Hill for each age group.

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 Gold Hill Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Gold Beach by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Gold Beach. The dataset can be utilized to understand the population distribution of Gold Beach by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Gold Beach. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Gold Beach.

Key observations

Largest age group (population): Male # 50-54 years (146) | Female # 65-69 years (187). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Gold Beach population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Gold Beach is shown in the following column.
• Population (Female): The female population in the Gold Beach is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Gold Beach for each age group.

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 Gold Beach Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Gold Bar by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Gold Bar. The dataset can be utilized to understand the population distribution of Gold Bar by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Gold Bar. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Gold Bar.

Key observations

Largest age group (population): Male # 30-34 years (123) | Female # 20-24 years (108). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Gold Bar population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Gold Bar is shown in the following column.
• Population (Female): The female population in the Gold Bar is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Gold Bar for each age group.

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 Gold Bar Population by Gender. You can refer the same here

Information on the amount of gold that is available across various U.S. Treasury-maintained locations, as well as data on the weight and book value of these gold reserves.

This dataset is part of the research project "All That Glitters Is Not Gold? Approaching the Sub-National and Spatial Impact of a Gold Rush and Policy Changes", funded by the Environment for Development Initiative (EfD). It includes socio-economic data from over 1,000 municipalities in Colombia, covering mining royalty revenues, forest cover and deforestation, and gold production. The dataset is longitudinal, meaning that for most variables, values are reported for 2001 to 2020. The data was collected from secondary data sources (all public sources, listed in the data description documents) and compiled in a single dataset. There are 118 variables and 21920 cases, each case being a municipality for each of the 20 years.

Aerial survey of the Gold Harbour elephant seal colony, Mirounga leonina, during the 2023/24 season conducted using a fixed-wing remotely piloted aerial system (RPAS).

The aerial survey was conducted as part of the Darwin Plus (DPLUS) 214 project: Southwest Atlantic Elephant Seal Population Assessment (SAESPA).

Dataset includes the original images and log files, post-processed imagery data, along with the resulting georeferenced DSM (digital surface model) and an orthorectified mosaic of the imagery.

This dataset is from flight number DPLUS_214_32 which was carried out on 2024-11-10.

This work was supported by the Overseas Territories Environment and Climate Fund under Grant Darwin Plus ref: DPLUS214: Southwest Atlantic Elephant Seal Population Assessment (SAESPA).

Historical dataset of the 12 month LIBOR rate back to 1986. The London Interbank Offered Rate is the average interest rate at which leading banks borrow funds from other banks in the London market. LIBOR is the most widely used global "benchmark" or reference rate for short term interest rates.

Second-Hand Fashion Dataset

Update Sep. 19th, 2024

• Some problematic and duplicate images have been removed from version 2.- All "gold dataset" data from station1 and station3 has been moved to a single test100 folder.- JSON errors have been fixed - all JSON files should be parsed correctly now.

The new dataset has 31,638 items (+ about 100 items in test100 folder) instead of the 31,997 items in version 2.

Overview

The dataset originates from projects focused on the sorting of used clothes within a sorting facility. The primary objective is to classify each garment into one of several categories to determine its ultimate destination: reuse, reuse outside Sweden (export), recycling, repair, remake, or thermal waste.

The dataset has 31,638 clothing items, a massive update from the 3,000 items in version 1. The dataset collection started under the Vinnova funded project "AI for resource-efficient circular fashion" in Spring, 2022 and involves collaboration among three institutions: RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB. The dataset has received further support through the EU project, CISUTAC (cisutac.eu).

Project page

• Webpage: second-hand-fashion- Contact: farrukh.nauman@ri.se

Dataset Details

• The dataset contains 31,638 clothing items, each with a unique item ID in a datetime format. The items are divided into three stations: station1, station2, and station3. The station1 and station2 folders contain images and annotations from Wargön Innovation AB, while the station3 folder contains data from Myrorna AB. Each clothing item has three images and a JSON file containing annotations.

• Three images are provided for each clothing item: 1. Front view. 2. Back view. 3. Brand label close-up. About 4000-5000 brand images are missing because of privacy concerns: people's hands, faces, etc. Some clothing items did not have a brand label to begin with.

• Image resolutions are primarily in two sizes: 1280x720 and 1920x1080. The background of the images is a table that used a measuring tape prior to January 2023, but later images have a square grid pattern with each square measuring 10x10 cm.

• Each JSON file contains a list of annotations, some of which require nuanced interpretation (see labels.py for the options): - usage: Arguably the most critical label, usage indicates the garment's intended pathway. Options include 'Reuse,' 'Repair,' 'Remake,' 'Recycle,' 'Export' (reuse outside Sweden), and 'Energy recovery' (thermal waste). About 99% of the garments fall into the 'Reuse,' 'Export,' or 'Recycle' categories. - trend: This field refers to the general style of the garment, not a time-dependent trend as in some other datasets (e.g., Visuelle 2.0). It might be more accurately labeled as 'style.' - material: Material annotations are mostly based on the readings from a Near Infrared (NIR) scanner and in some cases from the garment's brand label. - Damage-related attributes include: - condition (1-5 scale, 5 being the best) - pilling (1-5 scale, 5 meaning no pilling) - stains, holes, smell (each with options 'None,' 'Minor,' 'Major'). Note: 'holes' and 'smell' were introduced after November 17th, 2022, and stains previously only had 'Yes'/'No' options. For station1 and station2, we introduced additional damage location labels to assist in damage detection:

    "damageimage": "back",
    "damageloc": "bottom left",
    "damage": "stain ",
    "damage2image": "front",
    "damage2loc": "None",
    "damage2": "",
    "damage3image": "back",
    "damage3loc": "bottom right",
    "damage3": "stain"
  
  Taken from `labels_2024_04_05_08_47_35.json` file. Additionally, we annotated a few hundred images with bounding box annotations that we aim to release at a later date.  - `comments`: The comments field is mostly empty, but sometimes contains important information about the garment, such as a detailed text description of the damage. 
  

• Whenever possible, ISO standards have been followed to define these attributes on a 1-5 scale (e.g., pilling).

• Gold dataset: 100 garments were annotated multiple times by different annotators for annotator agreement comparisons. These 100 garments are placed inside a separate folder test100.

• The data has been annotated by a group of expert second-hand sorters at Wargön Innovation AB and Myrorna AB.

• Some attributes, such as price, should be considered with caution. Many distinct pricing models exist in the second-hand industry: - Price by weight - Price by brand and demand (similar to first-hand fashion) - Generic pricing at a fixed value (e.g., 1 Euro or 10 SEK) Wargön Innovation AB does not set the prices in practice and their prices are suggestive only (station1 and station2). Myrorna AB (station3), in contrast, does resale and sets the prices.

Comments

• We received feedback on our version 1 that some images were too blurry or had poor lighting. The image quality has slightly improved, but largely remains similar to release 1. - Some users did not prefer a tar.gz format that we uploaded in version 1 of the dataset. We have now switched to .zip for convenience.- Extra care was taken not to leak personal information. This is why you will not see any entries for annotator attribute in the JSON files in station1/sep2023 since people used their real names. Since then, we used internally assigned IDs. - Many brand images contained people's hands, faces, or other personal information. We have removed about 4000-5000 brand images for privacy reasons. - Please inform us immediately if you find any personal information revelations in the dataset: - Farrukh Nauman (RISE AB): farrukh.nauman@ri.se, - Susanne Eriksson (Wargön Innovation AB): susanne.eriksson@wargoninnovation.se, - Gabriella Engstrom (Wargön Innovation AB): gabriella.engstrom@wargoninnovation.se.

We went through 100k images four times to ensure no personal information is leaked, but we are human and can make mistakes.

Partners

The data collection for this dataset has been carried out in collaboration with the following partners:

1. RISE Research Institutes of Sweden AB: RISE is a leading research institute dedicated to advancing innovation and sustainability across various sectors, including fashion and textiles.

2. Wargön Innovation AB: Wargön Innovation is an expert in sustainable and circular fashion solutions, contributing valuable insights and expertise to the dataset creation.

3. Myrorna AB: Myrorna is Sweden's oldest chain of stores for collecting clothes and furnishings that can be reused.

License

CC-BY 4.0. Please refer to the LICENSE file for more details.

Acknowledgments

This dataset was made possible through the collaborative efforts of RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB, with funding from Vinnova and support from the EU project CISUTAC. We extend our gratitude to all the expert second-hand sorters and annotators who contributed their expertise to this project.