Automated Author ProfilePeterson, Ben
Peterson, Ben
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 6.9 (sum of 13 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/344/6, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org.This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-ntl&identifier=349&revision=4The abstract below was extracted from the Level 0 data package and is included for context:
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project, contact EDI or see https://environmentaldatainitiative.org.This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-ntl&identifier=349&revision=2The abstract below was extracted from the Level 0 data package and is included for context:
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
No description available
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabeth ;
- Wolf, Georgia ;
- Schmitz, Samuel
No description available
Authors
- McMahon, Katherine ;
- Jones, Stuart ;
- Shade, Ashley ;
- Newton, Ryan ;
- Read, Emily ;
- Beversdorf, Lucas ;
- Rohwer, Robin ;
- Peterson, Ben ;
- Linz, Alexandra ;
- McDaniel, Elizabet ;
- Wolf, Georgia ;
- Schmitz, Samuel