Ben Ruddell – Associate Professor of Hydrology
Email: bruddell at asu dot edu
Office Phone: 480-727-5123
Cell Phone: 217-649-2511
Airzona State University
App Idea: Staff Gauge
This is a front end App for citizen scientists to upload and visualize staff gauge hydrology data. A team of researchers is putting together a citizen scientist network in which volunteers will send in wetland and stream water stage data from sites places on trails, in parks, and along rivers around the world. The staff gauge is a simple visual target that indicates water level using a red and white striped pole. We need an application that allows volunteers to take a picture of the gauge, and upload the water level along with a timestamp, the gauge number, and (optionally) the photograph to a web server. The application will then provide the user feedback by displaying their observation along with other users’ data using a hydrograph. The application needs to be very simple and robust and user friendly, and it needs to utilize a standard community back-end database to handle and publish the observations in a format where the scientific community can access them.
David Flasphor – Professor of Forest Resources and Environmental Science
Email: djflaspo at mtu.edu
Office Phone: 906-487-3608
Cell Phone: 906-370-1122
Michigan Technological University
App Idea: Dead Bird App
This application would function to allow users to document and identify bird mortality events. Approximately 500 million birds are killed in the US each year from window collisions alone. A similar number are killed by outdoor cats and millions more are killed by vehicle collisions. All of these anthrpogentic sources of mortality are additive beyond the threats that birds evolved with for millennia and thus are a great cause for concern and a potential cause of population declines. Among wildlife, birds are among the most recognized and easily observed and birdwatching and feeding is a pastime for tens of millions of people in the US alone. This app seeks to utilize this motivated and engaged user group to generate data on the sources, frequencies, and species-specific patterns of human-causes bird mortality. Spatially explicit locations, times and species identity can be collected by anyone with a smart phone and uploaded into a database that could be used to generate maps of mortality “hot spots”, temporal patterns of mortality, and management options to reduce mortality.
Thursday, 1/21/2016 at 5:00 PM EDT (4:00 PM CDT)
Tuesday, 1/26/2015 at 5:00 PM EDT(4:00 PM CDT)
By “Go To Meeting”:
Dr. Flasphor is in Mexico the first half of this semester, so cannot use his phone, but hopes to have internet access. Confirm the meeting early and use “Go To Meeting” conference calling app.
Gregory Waite – Associate Professor of Geology and Mining Engineering and Science
Email: gpwaite at mtu dot edu
Office Phone: 906-487-3554
Department of Geological Mining Engineering and Sciences
Michigan Technological University
App Idea: Pacaya volcano activity monitor (Volcán Pacaya Monitor)
Pacaya volcano is a persistently active, open-vent volcano only 30 km from the capital of Guatemala. A moderate eruption in May 2010 ejected enough ash toward the city that the airport was closed for days. Smaller explosive eruptions occur more frequently along with basalt lava flows out the sides of the main cone. Even when there is not an eruption ongoing, the constant emission of hot, magmatically derived gases from the vent and fumaroles are reminders that magma is close to the surface. In addition to the visible activity, geophysical and geochemical modeling demonstrates that the volcano has a shallow magmatic system that changes on the timescale of weeks to months. Michigan Tech researchers have been studying Pacaya for decades, but have not had good daily observation data to aid in the interpretation of geophysical data. A new GPS and seismic monitoring network is being installed now (winter of 2015-16) and will allow for measurements of the activity in real time, but more information is needed in order to properly model and inform hazard mitigation agencies. Because Pacaya is in a national park and is a popular tourist destination, guides lead tourists to volcanic features daily. The objective of this app will be to provide a means for these guides, as well as the tourists, to make observations of the activity and easily track changes through time. By carefully tracking the volcano’s activity through the visual observations, this app will allow for a better interpretation of subsurface activity, from magma migration, to rainwater interactions with the shallow hydrothermal system.
Robert Manson – Professor of Ecology
Email: robert.manson at inecol dot mx
Instituto de Ecología, A.C. (federal research institution in Mexico)
App Idea: Roya Survey
The Roya Survey App seeks to provide feedback to scientists working with long-term climate date to generate models predicting levels of risk for infection of coffee farms by the coffee rust fungus in Mexico. The app will allow coffee farmers to register and then provide several photos and a personal estimation of the degree of coffee rust infection in their farms that will then be compared to existing model predictions to help refine them. In exchange, farms will be able to send additional photos of other pests and diseases in their farms and a request for help in identifying them and obtaining suitable control measures.
Andrew Storer – Professor of Forestry
Email: storer at mtu dot edu
School of Forest Resources and Environmental Science
Michigan Technological University
App Idea: Ant Mound Mapper
Very little information is available on the abundance and distribution of red wood ants and other mound forming species in North America. While North America has 24 species or sub-species of red wood ant (the Formica rufa group), only five of these species are reported to build large mounds that are characteristic of this group in Europe and Asia. However, in areas of North America where European red wood and species have been introduced, they have constructed large organic mounds and become dominant components of the forest floor fauna.
A first step to developing a research project that investigates the reasons for the lack of organic mound forming ants is to get a better understanding of the distribution of mounds of organic origin and of mineral origin in different parts of the country. There is an opportunity for citizen science project using an app to develop maps of where ant mounds are located, and to document where there is no evidence of mound forming ants.
Using an appropriate app, it is proposed that middle school or high school science classes can conduct investigations of the occurrence of ant mounds in school forests or other forested areas in proximity to schools. The data collected can be spatially referenced, and include photographs of the ecological setting, of the undisturbed mound, and of limited disturbance of mounds to determine whether or not they are organic or mineral in origin.
Dean Pentcheff – Research Associate Marine Biologist
Email: pentcheff at gmail dot com
Office phone: 213-763-3217
cell phone: 310-948-0341
Natural History Museum of Los Angeles County
App Idea: Crab Shack Kitchen
We’ll start with a little background first, then the app idea itself. Research museums have specimens. A lot of specimens. So many, in fact, that most of them are not electronically recorded anywhere: the only way we know if we have, say, a crab of a particular species or from a particular Pacific island, is to go to the shelves and look. That also means that no one outside the institution can discover what we have in the research collection, no matter how useful it might be to their research project.
We’re trying to catch up and “digitize” the specimens — capture the key information about each and every one, but there are far more specimens than time and people in the museum can handle. So we hooked up with the “Notes From Nature” (NfN) group (http://notesfromnature.org) to give us some help on a pilot project. We (in the research museum) developed a quick process to take a photograph of the labels that accompany each specimen. We put those images out on the NfN website with a form, soliciting the interested public to transcribe information into data fields on a web form. The idea is that, using the distributed labor of transcribers around the world, we can build a dataset that will allow us to populate a database of specimens more quickly than we could if we simply sat down and started typing.
This initial pilot project was to digitize each of the thousand or so lots (a lot is one or more specimens collected at the same time and location) we have of crabs in the family Cancridae (which includes some fun edibles, such as Dungeness crab). The NfN system gets four independent transcriptions of each label photograph. That gives us a dataset with four records per specimen lot, each with over a dozen data fields. Our challenge is to take those four records and assemble a single completed data record for input to our specimen database, and to do it in a way that’s quicker than if we just sat down and did the whole data entry job ourselves.
Therefore, what we need is an app that scientists can use to quickly examine all four transcription records from each specimen lot (along with the label photo from the lot), pick-and-choose which data entries in which records should be used to assemble the single completed record, and do some final editing on that completed record.
Because of the nature of the data on the specimen labels, there are ambiguities that lead to “issues” in the incoming data. For example, there are data fields for each of several kinds of numbers that could be on the labels, and it’s easy for transcribers to type a number into the wrong field. Even if transcribers enter the “same” label data into the same field on the form, they may do it slightly differently, inserting or omitting spaces, for example. One data field is for everything that didn’t map nicely to one of the regular data fields, so different transcribers may enter the same “leftover” text, but in a different order.
Some concerns and ideas we have include: highlighting similar (or different?) entries in the same field across the records, automatically creating consensus text in the completed record when there’s no ambiguity, permitting the researcher to cross-assign text from one field in a data record to a different field in the completed record, and in general making the entire process as quick as possible — quicker than the fallback strategy of just typing in the data ourselves.
Sunday, 1/24/2016 at 6:00 PM EDT (3:00 PM PDT)
Wednesday, 1/27/2016 at 6:00 PM EDT (3:00 PM PDT)