Science in hand: how art and craft can boost reproducibility

We — a surgeon, a research nurse and a synthetic chemist — looked beyond science to discover how people steeped in artistic skills might help to close this 'haptic gap', the deficit in skills of touch and object manipulation. We have found that craftspeople and performers can work fruitfully alongside scientists to address some of the challenges. We have also discovered striking similarities between the observational skills of an entomologist and an analytical chemist; the dexterity of a jeweller and a microsurgeon; the bodily awareness of a dancer and a space scientist; and the creative skills of a scientific glassblower, a reconstructive surgeon, a potter and a chef.

Data Pallets: Containerizing Storage For Reproducibility and Traceability

Trusting simulation output is crucial for Sandia's mission objectives. We rely on these simulations to perform our high-consequence mission tasks given national treaty obligations. Other science and modeling applications, while they may have high-consequence results, still require the strongest levels of trust to enable using the result as the foundation for both practical applications and future research. To this end, the computing community has developed workflow and provenance systems to aid in both automating simulation and modeling execution as well as determining exactly how was some output was created so that conclusions can be drawn from the data. Current approaches for workflows and provenance systems are all at the user level and have little to no system level support making them fragile, difficult to use, and incomplete solutions. The introduction of container technology is a first step towards encapsulating and tracking artifacts used in creating data and resulting insights, but their current implementation is focused solely on making it easy to deploy an application in an isolated "sandbox" and maintaining a strictly read-only mode to avoid any potential changes to the application. All storage activities are still using the system-level shared storage. This project explores extending the container concept to include storage as a new container type we call \emph{data pallets}. Data Pallets are potentially writeable, auto generated by the system based on IO activities, and usable as a way to link the contained data back to the application and input deck used to create it.

A Model-Centric Analysis of Openness, Replication, and Reproducibility

The literature on the reproducibility crisis presents several putative causes for the proliferation of irreproducible results, including HARKing, p-hacking and publication bias. Without a theory of reproducibility, however, it is difficult to determine whether these putative causes can explain most irreproducible results. Drawing from an historically informed conception of science that is open and collaborative, we identify the components of an idealized experiment and analyze these components as a precursor to develop such a theory. Openness, we suggest, has long been intuitively proposed as a solution to irreproducibility. However, this intuition has not been validated in a theoretical framework. Our concern is that the under-theorizing of these concepts can lead to flawed inferences about the (in)validity of experimental results or integrity of individual scientists. We use probabilistic arguments and examine how openness of experimental components relates to reproducibility of results. We show that there are some impediments to obtaining reproducible results that precede many of the causes often cited in literature on the reproducibility crisis. For example, even if erroneous practices such as HARKing, p-hacking, and publication bias were absent at the individual and system level, reproducibility may still not be guaranteed.

Reproducible Publications at AGILE Conferences

The council of the Association of Geographic Information Laboratories in Europe (AGILE) provides funding to support a new AGILE initiative. Reproducible Publications at AGILE Conferences" will develop protocols for publishing reproducible research in AGILE conference publications. The aim is to support and improve the way we describe our science and to enhance the usefulness of AGILE conference publications to the wider community. The potential benefits of this include greater research transparency, enhanced citations of published articles and increased relevance of the conference in the field. The funding will support a workshop attended by domain experts to develop author and reviewer guidelines that will be presented at the AGILE 2019 conference. The initiative members are Daniel Nüst (Institute for Geoinformatics, University of Münster, Münster, Germany), Frank Ostermann (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands), Rusne Sileryte (Faculty of Architecture and the Built Environment, Delft University of Technology, Delft, The Netherlands), Carlos Granell (Institute of New Imaging Technologies, Universitat Jaume I de Castellón, Castellón, Spain), and Barbara Hofer (Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria)."

Conducting Replication Studies With Confidence

Although essential to the development of a robust evidence base for nurse educators, the concepts of replication and reproducibility have received little attention in the nursing education literature. In this Methodology Corner installment, the concepts of study replication and reproducibility are explored in depth. In designing, conducting, and documenting the findings of studies in nursing education, researchers are encouraged to make design choices that improve study replicability and reproducibility of study findings. [J Nurs Educ. 2018;57(11):638–640.] There has been considerable discussion in the professional literature about questionable research practices that raise doubt about the credibility of research findings (Shrout & Rodgers, 2018) and that limit reproducibility of research findings (Shepherd, Peratikos, Rebeiro, Duda, & McCowan, 2017). This discussion has led to what scientists term as a replication crisis (Goodman, Fanelli, & Ioannidis, 2016). Although investigators in various disciplines have provided suggestions to address this crisis (Alvarez, Key, & Núñez, 2018; Goodman et al., 2016; Shrout & Rodgers, 2018), similar discussions or reports of replication within nursing education literature are limited, despite a call for replication studies (Morin, 2016). Consequently, the focus of this article is on replication and reproducibility. The topic is important, given that the hallmark of good science is being able to replicate or reproduce findings (Morin, 2016). Replication serves to provide “stability in our knowledge of nature” (Schmidt, 2009, p. 92).