The need for sound ecological science has escalated alongside the rise of the information age and “big data” across all sectors of society. Big data generally refer to massive volumes of data not readily handled by the usual data tools and practices and present unprecedented opportunities for advancing science and informing resource management through data‐intensive approaches. The era of big data need not be propelled only by “big science” – the term used to describe large‐scale efforts that have had mixed success in the individual‐driven culture of ecology. Collectively, ecologists already have big data to bolster the scientific effort – a large volume of distributed, high‐value information – but many simply fail to contribute. We encourage ecologists to join the larger scientific community in global initiatives to address major scientific and societal problems by bringing their distributed data to the table and harnessing its collective power. The scientists who contribute such information will be at the forefront of socially relevant science – but will they be ecologists?

The time is right for biologists to post their research findings onto preprint servers

Data “publication” seeks to appropriate the prestige of authorship in the peer-reviewed literature to reward researchers who create useful and well-documented datasets. The scholarly communication community has embraced data publication as an incentive to document and share data. But, numerous new and ongoing experiments in implementation have not yet resolved what a data publication should be, when data should be peer-reviewed, or how data peer review should work. While researchers have been surveyed extensively regarding data management and sharing, their perceptions and expectations of data publication are largely unknown. To bring this important yet neglected perspective into the conversation, we surveyed ∼ 250 researchers across the sciences and social sciences– asking what expectations“data publication” raises and what features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication. We found that researcher expectations of data publication center on availability, generally through an open database or repository. Few respondents expected published data to be peer-reviewed, but peer-reviewed data enjoyed much greater trust and prestige. The importance of adequate metadata was acknowledged, in that almost all respondents expected data peer review to include evaluation of the data’s documentation. Formal citation in the reference list was affirmed by most respondents as the proper way to credit dataset creators. Citation count was viewed as the most useful measure of impact, but download count was seen as nearly as valuable. These results offer practical guidance for data publishers seeking to meet researcher expectations and enhance the value of published data.

The movement to bring datasets into the scholarly record as first class research products (validated, preserved, cited, and credited) has been inching forward for some time, but now the pace is quickening. As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention. Data publication implementations differ in a variety of factors, including the kind of documentation, the location of the documentation relative to the data, and how the data is validated. Publishers may present data as supplemental material to a journal article, with a descriptive "data paper," or independently. Complicating the situation, different initiatives and communities use the same terms to refer to distinct but overlapping concepts. For instance, the term means that the data is publicly available and citable to published virtually everyone, but it may or may not imply that the data has been peer-reviewed. In turn, what is meant by data peer review is far from defined; standards and processes encompass the full range employed in reviewing the literature, plus some novel variations. Basic data citation is a point of consensus, but the general agreement on the core elements of a dataset citation frays if the data is dynamic or part of a larger set. Even as data publication is being defined, some are looking past publication to other metaphors, notably "data as software," for solutions to the more stubborn problems.This article is included in the Science Policy gateway. ResearchThis article is included in the Data: Use and Reuse collection. Amendments from Version 2This version no longer presents three models for data publication based on documentation. Instead, we treat documentation as an essential feature and discuss three forms of documentation in parallel with forms of availability, citation, and validation. The figure has been updated to reflect this reorganization.Numerous minor additions, corrections and clarifications were made throughout in response to referee and reader comments. Most significantly, the discussions of paper-independent documentation and validation have been expanded, as has the concluding "beyond data publication". See referee reports REVISED What does data publication mean?The idea that researchers should share data to advance knowledge and promote the common good is an old one, but in recent years the conversation has shifted from sharing data to publishing data 1-3 . This shift in language stems from the conviction that datasets should join the scholarly record and be afforded the same first-class status as traditional research products like journal articles 4,5 . While many in the scholarly communication community share this goal, different people and organizations often refer to different things with the phrase data publication. Lawrence et al. (2011) define formal data Publication (upper-c...

Abstract. Data management is a timely and increasingly important topic for ecologists. Recent funder mandates requiring data management plans, combined with the data deluge that faces scientists, make education about data management critical for any future ecologist. In this study, we surveyed instructors of general ecology courses at 48 major institutions in the United States. We chose instructors at institutions that are likely to train future ecologists, and therefore, are most likely to influence the trajectory of data management education in this field. The survey queried instructors about institution and course characteristics, the extent to which data-related topics are included in their courses, the barriers to their teaching these topics, and their own personal beliefs and values associated with data management and stewardship. We found that, in general, data management topics are not being covered in undergraduate ecology courses for a wide range of reasons. Most often, instructors cited a lack of time and a lack of resources as barriers to teaching data management. Although data are used for instruction at some point in the majority of the courses surveyed, good data management practices and a thorough understanding of the importance of data stewardship are not being taught. We offer potential explanations for this and suggestions for improvement.

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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. Published by Elsevier B.V.

This community perspective piece calls on publishers to promote and contribute to increasing access to data in their role with eight simple recommendations and example action items.