Projects

Current and past research projects conducted by the Open Knowledge Lab.

Biocubes

Every student has measurable biodiversity underfoot, within walking distance. With the right tools, they could participate in research and monitoring projects that could use their contributed observations on a regional or national scale to answer questions about sustainability. The Biocube project broadens the scope of citizen science by promoting observation of a wider array of organisms, fostering an ecosystem view rather than a species-specific perspective, and providing technological infrastructure to increase its scientific and educational impact. This project aims to provide greater public access to STEM learning experiences while laying the groundwork for data exchange as a step on the way to increasing the scientific impact of citizen science data. Teachers interested in requesting a Biocube kit for classroom use can contact our Smithsonian partners at biocube@si.edu. The Biocubes project involves numerous partners and collaborators working to recruit and train science teachers to use biocubes in their classrooms, build the data infrastructure to alert subscribers to newly available data matching their interests and inform data creators about the use of the data they contribute, and understand the needs of stakeholders in this data sharing ecosystem. Our initial phase of research is exploring the role that the iNaturalist social networking platform plays as a third-party provider of community-based data validation services and data management infrastructure for smaller projects like Biocubes. We are interested in learning whether utilizing platforms like iNaturalist provide additional value for scientific research that justify the tradeoffs inherent in adapting scientific protocols and participation processes to use available tools. There is a clear need for such platforms, but the citizen science practitioner community does not yet have...

Climate Indicators and Data Provenance

How does a scientist know whether an available data set can support their work? This study examines how researchers from different disciplines and practical contexts (e.g., graduate students, faculty researchers, federal research scientists) use information about the sources and analysis of data, also known as provenance, when presented with indicators in an online system, addressing the research question: Can coupling climate-related indicators with data provenance support scientific innovation and science translation? This study draws on web credibility research as well as boundary object theory, which focuses on the role of artifacts (such as images) in translation and communication across the boundaries of social groups, as a theoretical lens to inform and direct our inquiry. In this pilot study, we are examining the way that such artifacts can support innovation and translation in the National Climate Indicator System (NCIS). Through a multi-stage research design, we hope to discover principles for optimizing the presentation of data for scientific advancements and translation. Packaging an integrated data product (indicators) with its provenance seems a valuable strategy for improving the ability of researchers to creatively consider the utility of data and information from other domains for use in their own work. This research is a collaboration with Dr. Melissa Kenney of the Earth System Science Interdisciplinary Center, supported by a seed grant from the UMD ADVANCE Program for Inclusive Excellence (NSF award HRD 1008117). Please like &...

Citizen Science Evaluation & Planning

In collaboration with the Smithsonian Environmental Research Center (SERC), we are testing evaluation tools designed to establish contextually-appropriate means of evaluating scientific productivity. Due to the diversity of goals and practices, measuring science outcomes in citizen science projects requires a holistic approach, so we are developing evaluation and planning procedures suited to application across a variety of contexts. At SERC, we can work with a diverse range of citizen science projects to improve the robustness and generalizability of a science outcomes inventory and planning toolkit that will be useful to the broader citizen science community as well. Citizen science can be considered both a methodology and a phenomenon; in this study, we focus on its methodological characteristics through the contextualized evaluation and planning process. As a phenomenon, we focus on understanding these projects’ evolutionary patterns and the impact of key decisions on project development, addressing these research questions: What are the typical stages of project development and longitudinal patterns of project evolution in citizen science projects? What events or conditions influence project management decisions in citizen science projects? How does structured evaluation of project outputs support project evolution and decision making? The products of this research will include improved citizen science project management and evaluation processes. We also anticipate new insights into project dynamics and resource requirements that can be used to establish reasonable, evidence-based resource allocations and performance expectations for local-to-regional field-based citizen science projects, supporting more effective project management and improved sustainability. Please like &...

Open Collaboration Data Factories

The Open Collaboration Data Factories (OCDF) initiative focuses on actively prototyping open knowledge infrastructures as solutions to gaps in research approaches and methods in the study of knowledge creation in open online communities, such as those that create Wikipedia, open source software, and citizen science. We are building a community of scholars who address differences in research aims, data, and methods to enable a new, interdisciplinary knowledge production. The Open Knowledge Lab has leveraged  student course assignments to develop a prototype research data directory with detailed documentation of openly available data for the study of online communities. Information Management graduate students in Dr. Wiggins’ INFM 600 (Information Environments) course learn valuable professional skills by searching, evaluating, interrogating, documenting, licensing, and citing open data while creating value-added resources for scientific research on open collaboration. Please like &...

Citizen Science Data Usage

    To understand the potential value and applications of freely available, carefully curated open citizen science data, our research team is working with partners from the University of Michigan and the Cornell Lab of Ornithology on a small study of eBird data users’ practices and outcomes. Survey responses are currently under analysis; respondents documented a broad range of uses for eBird data across distinct contexts, including numerous conservation applications, academic research studies, educational uses at every level, and leisure-related uses, such as record-keeping in the birding community. The inclusion of effort information—documentation of the time and place that observations were made—was considered critical for most uses of the data. Please like &...