Universities can improve academic services through wider recognition of altmetrics and alt-products.

As altmetrics gain traction across the scholarly community, publishers and academic institutions are seeking to develop standards to encourage wider adoption. Carly Strasser provides an overview of why altmetrics are here to stay and how universities might begin to incorporate altmetrics into their own services. While this process might take some time, institutions can begin by encouraging their researchers to recognize the importance of all of their scholarly work (datasets, software, etc)

DMPTool: Current Status & Future Directions

Carly Strasser, PhD, is a data curation specialist at the California Digital Library, part of the University of California Office of the President. She is involved in the development and implementation of many of the UC Curation Center\u27s services, including the DMPTool, which is software to guide researchers in creating a data management plan. In this presentation, Carly discusses tools that can be used to support data management

Metapopulation dynamics of the softshell clam, Mya arenaria

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2008In this dissertation, I explored metapopulation dynamics and population connectivity, with a focus on the softshell clam, Mya arenaria. I first worked towards developing a method for using elemental signatures retained in the larval shell as a tag of natal habitat. I designed and implemented an experiment to determine whether existing methods commonly used for fishes would be applicable to bivalves. I found that the instrumentation and setup I used were not able to isolate and measure the first larval shell of M. arenaria. In concert with developing this method for bivalves, I reared larval M. arenaria in the laboratory under controlled conditions to understand the environmental and biological factors that may influence elemental signatures in shell. My results show that growth rate and age have significant effects on juvenile shell composition, and that temperature and salinity affect larval and juvenile shell composition in variable ways depending on the element evaluated. I also examined the regional patterns of diversity over the current distribution of M. arenaria using the mitochondrial gene, cytochrome oxidase I (COI). I found minimal variability across all populations sampled, suggesting a recent population expansion in the Northwest Atlantic. Finally, I employed theoretical approaches to understand patch dynamics in a two-patch metapopulation when one patch is of high quality and the other low quality. I developed a matrix metapopulation model and compared growth rate elasticity to patch parameters under variable migration scenarios. I then expanded the model to include stochastic disturbance. I found that in many cases, the spatial distribution of individuals within the metapopulation affects whether growth rate is most elastic to parameters in the good or bad patch.Financial support was provided by the National Defense Science and Engineer- ing Graduate Fellowship; the WHOI Academic Programs O±ce; NSF grants OCE- 0326734, OCE-0215905, OCE-0349177, DEB-0235692, DMS-0532378, and ATM-0428122; and by NOAA National Sea Grant College Program O±ce, Department of Commerce, under Grant No. NA86RG0075 (Woods Hole Oceanographic Institution Sea Grant Project No. R/0-32), and Grant No. NA16RG2273 (WHOI Sea Grant Project No. R/0-35)

DMPTool 2: Expanding Functionality for Better Data Management Planning

Scholarly researchers today are increasingly required to engage in a range of data management planning activities to comply with institutional policies, or as a precondition for publication or grant funding. The latter is especially true in the U.S. in light of the recent White House Office of Science and Technology Policy (OSTP) mandate aimed at maximizing the availability of all outputs – data as well as the publications that summarize them – resulting from federally-funded research projects. To aid researchers in creating effective data management plans (DMPs), a group of organizations – California Digital Library, DataONE, Digital Curation Centre, Smithsonian Institution, University of Illinois Urbana-Champaign, and University of Virginia Library – collaborated on the development of the DMPTool, an online application that helps researchers create data management plans. The DMPTool provides detailed guidance, links to general and institutional resources, and walks a researcher through the process of generating a comprehensive plan tailored to specific DMP requirements. The uptake of the DMPTool has been positive: to date, it has been used by over 6,000 researchers from 800 institutions, making use of more than 20 requirements templates customized for funding bodies. With support from the Alfred P. Sloan Foundation, project partners are now engaged in enhancing the features of the DMPTool. The second version of the tool has enhanced functionality for plan creators and institutional administrators, as well as a redesigned user interface and an open RESTful application programming interface (API). New administrative functions provide the means for institutions to better support local research activities. New capabilities include support for plan co-ownership; workflow provisions for internal plan review; simplified maintenance and addition of DMP requirements templates; extensive capabilities for the customization of guidance and resources by local institutional administrators; options for plan visibility; and UI refinements based on user feedback and focus group testing. The technical work undertaken for the DMPTool Version 2 has been accompanied by a new governance structure and the growth of a community of engaged stakeholders who will form the basis for a sustainable path forward for the DMPTool as it continues to play an important role in research data management activities

DataShare: Empowering Researcher Data Curation

Researchers are increasingly being asked to ensure that all products of research activity – not just traditional publications – are preserved and made widely available for study and reuse as a precondition for publication or grant funding, or to conform to disciplinary best practices. In order to conform to these requirements, scholars need effective, easy-to-use tools and services for the long-term curation of their research data. The DataShare service, developed at the University of California, is being used by researchers to: (1) prepare for curation by reviewing best practice recommendations for the acquisition or creation of digital research data; (2) select datasets using intuitive file browsing and drag-and-drop interfaces; (3) describe their data for enhanced discoverability in terms of the DataCite metadata schema; (4) preserve their data by uploading to a public access collection in the UC3 Merritt curation repository; (5) cite their data in terms of persistent and globally-resolvable DOI identifiers; (6) expose their data through registration with well-known abstracting and indexing services and major internet search engines; (7) control the dissemination of their data through enforceable data use agreements; and (8) discover and retrieve datasets of interest through a faceted search and browse environment. Since the widespread adoption of effective data management practices is highly dependent on ease of use and integration into existing individual, institutional, and disciplinary workflows, the emphasis throughout the design and implementation of DataShare is to provide the highest level of curation service with the lowest possible technical barriers to entry by individual researchers. By enabling intuitive, self-service access to data curation functions, DataShare helps to contribute to more widespread adoption of good data curation practices that are critical to open scientific inquiry, discourse, and advancement

Spatially Explicit Data: Stewardship and Ethical Challenges in Science

Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of data stewardship and data sharing. Formal data management plans represent a new emphasis in research, enabling access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration

Contributions of high- and low-quality patches to a metapopulation with stochastic disturbance

© The Author(s), 2010. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Theoretical Ecology 5 (2012): 167-179, doi:10.1007/s12080-010-0106-9.Studies of time-invariant matrix metapopulation models indicate that metapopulation growth rate is usually more sensitive to the vital rates of individuals in high-quality (i.e., good) patches than in low-quality (i.e., bad) patches. This suggests that, given a choice, management efforts should focus on good rather than bad patches. Here, we examine the sensitivity of metapopulation growth rate for a two-patch matrix metapopulation model with and without stochastic disturbance and found cases where managers can more efficiently increase metapopulation growth rate by focusing efforts on the bad patch. In our model, net reproductive rate differs between the two patches so that in the absence of dispersal, one patch is high quality and the other low quality. Disturbance, when present, reduces net reproductive rate with equal frequency and intensity in both patches. The stochastic disturbance model gives qualitatively similar results to the deterministic model. In most cases, metapopulation growth rate was elastic to changes in net reproductive rate of individuals in the good patch than the bad patch. However, when the majority of individuals are located in the bad patch, metapopulation growth rate can be most elastic to net reproductive rate in the bad patch. We expand the model to include two stages and parameterize the patches using data for the softshell clam, Mya arenaria. With a two-stage demographic model, the elasticities of metapopulation growth rate to parameters in the bad patch increase, while elasticities to the same parameters in the good patch decrease. Metapopulation growth rate is most elastic to adult survival in the population of the good patch for all scenarios we examine. If the majority of the metapopulation is located in the bad patch, the elasticity to parameters of that population increase but do not surpass elasticity to parameters in the good patch. This model can be expanded to include additional patches, multiple stages, stochastic dispersal, and complex demography.Financial support was provided by the Woods Hole Oceanographic Institution Academic Programs Office; National Science Foundation grants OCE-0326734, OCE- 0215905, OCE-0349177, DEB-0235692, DEB-0816514, DMS- 0532378, OCE-1031256, and ATM-0428122; and by National Oceanic and Atmospheric Administration National Sea Grant College Program Office, Department of Commerce, under Grant No. NA86RG0075 (Woods Hole Oceanographic Institution Sea Grant Project No. R/0-32), and Grant No. NA16RG2273 (Woods Hole Oceanographic Institution Sea Grant Project No. R/0-35)

Growth rate and age effects on Mya arenaria shell chemistry: Implications for biogeochemical studies

This paper is not subject to U.S. copyright. The definitive version was published in Journal of Experimental Marine Biology and Ecology 355 (2008): 153-163, doi:10.1016/j.jembe.2007.12.022.The chemical composition of bivalve shells can reflect that of their environment, making them useful indicators of climate, pollution, and ecosystem changes. However, biological factors can also influence chemical properties of biogenic carbonate. Understanding how these factors affect chemical incorporation is essential for studies that use elemental chemistry of carbonates as indicators of environmental parameters. This study examined the effects of bivalve shell growth rate and age on the incorporation of elements into juvenile softshell clams, Mya arenaria. Although previous studies have explored the effects of these two biological factors, reports have differed depending on species and environmental conditions. In addition, none of the previous studies have examined growth rate and age in the same species and within the same study. We reared clams in controlled laboratory conditions and used solution-based inductively coupled plasma mass spectrometry (ICP-MS) analysis to explore whether growth rate affects elemental incorporation into shell. Growth rate was negatively correlated with Mg, Mn, and Ba shell concentration, possibly due to increased discrimination ability with size. The relationship between growth rate and Pb and Sr was unresolved. To determine age effects on incorporation, we used laser ablation ICP-MS to measure changes in chemical composition across shells of individual clams. Age affected incorporation of Mn, Sr, and Ba within the juvenile shell, primarily due to significantly different elemental composition of early shell material compared to shell accreted later in life. Variability in shell composition increased closer to the umbo (hinge), which may be the result of methodology or may indicate an increased ability with age to discriminate against ions that are not calcium or carbonate. The effects of age and growth rate on elemental incorporation have the potential to bias data interpretation and should be considered in any biogeochemical study that uses bivalves as environmental indicators.This work was supported by NSF project numbers OCE-0241855 and OCE-0215905

Qualitative data sharing and re-use for socio-environmental systems research: A synthesis of opportunities, challenges, resources and approaches

Researchers in many disciplines, both social and natural sciences, have a long history of collecting and analyzing qualitative data to answer questions that have many dimensions, to interpret other research findings, and to characterize processes that are not easily quantified. Qualitative data is increasingly being used in socio-environmental systems research and related interdisciplinary efforts to address complex sustainability challenges. There are many scientific, descriptive and material benefits to be gained from sharing and re-using qualitative data, some of which reflect the broader push toward open science, and some of which are unique to qualitative research traditions. However, although open data availability is increasingly becoming an expectation in many fields and methodological approaches that work on socio-environmental topics, there remain many challenges associated the sharing and re-use of qualitative data in particular. This white paper discusses opportunities, challenges, resources and approaches for qualitative data sharing and re-use for socio-environmental research. The content and findings of the paper are a synthesis and extension of discussions that began during a workshop funded by the National Socio-Environmental Synthesis Center (SESYNC) and held at the Center Feb. 28-March 2, 2017. The structure of the paper reflects the starting point for the workshop, which focused on opportunities, challenges and resources for qualitative data sharing, and presents as well the workshop outputs focused on developing a novel approach to qualitative data sharing considerations and creating recommendations for how a variety of actors can further support and facilitate qualitative data sharing and re-use. The white paper is organized into five sections to address the following objectives: (1) Define qualitative data and discuss the benefits of sharing it along with its role in socio-environmental synthesis; (2) Review the practical, epistemological, and ethical challenges regarding sharing such data; (3) Identify the landscape of resources available for sharing qualitative data including repositories and communities of practice (4) Develop a novel framework for identifying levels of processing and access to qualitative data; and (5) Suggest roles and responsibilities for key actors in the research ecosystem that can improve the longevity and use of qualitative data in the future.This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1052875