| NSF Org: |
SMA SBE Office of Multidisciplinary Activities |
| Recipient: |
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| Initial Amendment Date: | September 13, 2013 |
| Latest Amendment Date: | April 30, 2017 |
| Award Number: | 1338467 |
| Award Instrument: | Standard Grant |
| Program Manager: |
John Yellen
jyellen@nsf.gov (703)292-8759 SMA SBE Office of Multidisciplinary Activities SBE Directorate for Social, Behavioral and Economic Sciences |
| Start Date: | September 15, 2013 |
| End Date: | October 31, 2017 (Estimated) |
| Total Intended Award Amount: | $151,358.00 |
| Total Awarded Amount to Date: | $151,358.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
110 INNER CAMPUS DR AUSTIN TX US 78712-1139 (512)471-6424 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
TX US 78712-1532 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Data Infrastructure |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.075 |
ABSTRACT
A common challenge of data-intensive research in many scientific fields is the difficulty of pooling data in ways that support broad-scale comparative analysis. This is certainly the case for field studies of animal behavior, where investigators can seldom focus on more than one or a few species and locales. Comparative research in the behavioral sciences is also hindered by a lack of standards and transparency across research groups as well as a shortage of modern tools and technologies for collecting and managing behavioral data. This project will address these challenges developing strategies and technologies for behavioral research using the collective experience of database specialists, software developers, and field primatologists, a community chosen because it has a vibrant interest in these issues.
There are four key goals to this project:
1. To engage field primatologists and database specialists in developing open data standards that encompass the diversity of the discipline.
2. To create and test a software system for data collection and management that puts these standards into practice. The system will be easily customized and able to run on a variety of mobile devices. Additionally the plans and software source code for it will be published openly for others to review, use, and improve upon.
3. To develop additional software tools that will help behavioral researchers migrate existing data to work with this new system.
4. To encourage researchers and institutional librarians to develop a vision for long-term archiving and curation of behavioral data.
The project will also produce tools for data visualization and analysis, which should encourage investigators to incorporate real-time visual and statistical feedback into their research in both the field and laboratory. Because of the multidisciplinary nature of modern field primatology, this framework is expected to be broadly applicable to researchers from across the social, behavioral, economic, and natural sciences.
This project aims to build an interdisciplinary community of behavioral researchers involving both junior and established scholars. Its products will enable these researchers to collect data more quickly and efficiently while expanding the scope and utility of their data beyond their immediate research questions. Through workshops, tutorials, and documentation, community members will become increasingly data- and design-literate, which will encourage more comparative, "big data" projects and spur collaboration across disciplines. A working repository for behavioral data will help foster a culture of data-sharing among researchers. Through an extensive online presence, the project team will communicate with the public about the progress of this project and about the practice of fieldwork, laboratory work, and science in general. The open nature of the project will enable the public to freely adopt and modify any of this project's products for varied and novel purposes. Finally, because the majority of researchers involved in this project are fieldworkers and educators with influence both in the United States and abroad, the ideas and tools produced will be widely disseminated, providing opportunities for education, outreach, and community participation in science.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Primatology sits at the nexus of a number of disciplines in the behavioral sciences. The field shares a problem common to many integrative social sciences: a lack of standardization in data management, including in the vocabulary used to identify categories of data. Consequently, the same information may be encoded by different researchers in many different ways. In addition, behavioral researchers often rely on existing software tools for recording field observations without any technical standard for how their data are stored or disseminated. These factors make it difficult to compare results. In this research project, we sought to address these problems by developing:
- a community-derived body of data standards for behavioral research, including a set of vocabularies and technical specifications,
- data collection software for behavioral research in the field, along with a series of tools for data upload/download, visualization, and analysis, and
- a flexible online repository as a resource for uploading, downloading, and archiving data.
To accomplish our objectives, we formed the Ethoinformatics Working Group, which held meetings in November 2013 (St. Louis) and May 2015 (Austin). During these meetings, we canvassed the community to understand the breadth of their data, their data management practices, and other challenges in their work.
Based largely on community feedback, we developed a vocabulary, derived from the terms many of our project's participants were already using to describe behavioral observation and other field data. This vocabulary, which we call EthoCore (http://ethoinformatics.org/ethocore), extends an existing metadata standard, Darwin Core, that can be applied to a broad range of social science data. We are currently collaborating with a number of university libraries to use our vocabulary to connect major primatological data sources into a unified web-based discovery interface.
We also looked at the software that our primatology partners were using in the field to take notes, noting its strengths and weaknesses. We asked ourselves, could we develop software that primatologists could modify themselves? From this, with a team of software designers, we developed the interface for a new software tool, customized to our primatologists' needs.
We are strong advocates of technological selfdetermination. We believe in open source software and accessible tools because they make it possible for people to develop their own technology tools rather than to rely on professional developers. As part of our working group meetings, we explained to the community how databases work and how tools they are familiar with from the worldwide web can be used to create custom data management tools. In the course of this project, the software designers learned how behavioral scientists do their work, and the behavioral scientists learned how programmers do theirs. Furthermore, we developed a software framework that can be customized by behavioral researchers for their own needs, with little software training. It starts with a template describing a scientist's protocol for their observations, using the EthoCore vocabulary. That template describes not only the behaviors the scientist is looking for, but also the elements of the software used to capture the observations. For example, recording a "contact" with a monkey might include time, date, location, the monkey's age and sex, and what other monkeys are present. The software would require a time and date field, a map coordinate, text fields for the age and sex, and a list of other monkeys. From this description, our software framework generates a custom notetaking app for collecting these data, like the one shown in the attached figures.
Our software runs on a variety of handheld devices. It connects to a database on the internet, allowing researchers to download data collection protocols (called ethograms) from the database and to upload their records of observations when they return from the field. It also tracks their location, using either the built-in GPS receiver in the researcher's mobile device, or using an external GPS receiver. We've been testing it in the field, and we hope to continue developing it and sharing it with other behavioral scientists. You can learn more about it at http://www.ethoinformatics.org.
The most exciting and promising result of this project for us is not just the software, but the development of a common vocabulary for behavioral researchers to use for communicating their results with one another and a data protocol that supports the sharing and communication of those results. We are equally excited about the techniques we've developed to help nonprogrammers learn to build their own software tools. Beyond the end of the grant, we plan to continue the development of both our software and data protocols and to expand the data literacy training tools we have developed for our students and colleagues as part of this project.
Last Modified: 02/20/2018
Modified by: Anthony Di Fiore
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