Distributed Research Teams Research Articles

Nonreplicating synthetic mRNA vaccines: A journey through the European (Journal of Immunology) history.

The first worldwide article reporting that injections of synthetic nonreplicating mRNA could be used as a vaccine, which originated from a French team located in Paris, was published in the European Journal of Immunology (EJI) in 1993. It relied on work conducted by several research groups in a handful of countries since the 1960s, which put forward the precise description of eukaryotic mRNA and the method to reproduce this molecule in vitro as well as how to transfect it into mammalian cells. Thereafter, the first industrial development of this technology began in Germany in 2000, with the founding of CureVac, which stemmed from another description of a synthetic mRNA vaccine published in EJI in 2000. The first clinical studies investigating mRNA vaccines in humans were performed as collaboration between CureVac and the University of Tübingen in Germany as early as 2003. Finally, the first worldwide approved mRNA vaccine (an anti-COVID-19 vaccine) is based on the mRNA technologies developed by BioNTech since its 2008 foundation in Mainz, Germany, and earlier by the pioneering academic work of its founders. In addition to the past, present, and future of mRNA-based vaccines, the article aims to present the geographical distribution of the early work, how the development of the technology was implemented by several independent and internationally distributed research teams, as well as the controversies on the optimal way to design or formulate and administer mRNA vaccines.

Usage Experience and Capabilities of the VEGA-Science System

Currently, when satellite data volumes grow rapidly and exceed petabyte values and their quality provides reliable analysis of long-term time series, traditional data handling methods assuming local storage and processing may be impossible to implement for small or distributed research teams. Thus, new methods based on modern web technologies providing access to very large distributed data archives are gaining increasing importance. Furthermore, these new data handling solutions should provide not just access but also analysis and processing features, similar to desktop solutions. This paper describes the VEGA-Science web GIS—an open-access novel tool for satellite data processing and analysis. The overview of its architecture and basic technical components is given, but most attention is paid to examples of actual system application for various applied and research tasks. In addition, an overview of projects using the system is given to illustrate its versatility and further development directions are considered.

Addressing the Challenges of Online Video Analysis in Qualitative Studies: A Worked Example from Computational Thinking Research

In this paper, we share our approach and the process for qualitative analysis of online video data recorded during an after-school robotics program that emphasized computational thinking (CT). Online research strategies may be necessary for various reasons such as when working with a geographically distributed research team, when conducting research with students in an online program, or when resources are inaccessible due to campus closures like those experienced during the COVID-19 pandemic. We followed a three-stage process during qualitative analysis of the videos that included planning and setup, online analysis of videos, and structural coding of memos to explore patterns across the data. Analysis was conducted with a combination of technologies including Google Drive for collaborative coding online and NVivo to collate and summarize findings. The methods and process we describe are readily applicable to other research studies that include video as part of the data set.

Collaborative Creativity with eCiC

Students are often attentive highly motivated individuals who have good ideas which can provide successful solutions for all parties concerned, but mostly they have no way of bringing in and developing new ideas with other students in order to improve learning and educational processes. To enable collaborative creativity, the eCollaboration-Research Team at the Swiss Distance University of Applied Sciences has developed a solution whereby students or teachers can collaborate and nurture new creative ideas in a structured and guided way. In our solution, this nurturing takes place by means of a collaborative online process in which the “idea seed” will be “cultivated” during various interactive phases as defined by the eCIC method and supported by the eCIC online tool (eCiC = electronic Collaborative idea Cultivation). Together the method and tool constitute the eCIC system. The eCiC interaction method is a procedure which defines a creative collaboration session in three stages: 1) the setting up of a creative collaboration session, 2) ideas processing according to the “Stockalper model” as well as applying the Solution Finder Model (SFM) and 3) closing the creative collaboration session. Stage 2 contains the use of two relevant models, the “Stockalper Model” which guides the user through three different questions, symbolised by the moon (illuminate your way in the darkness), stars (search for new ideas) and sun (deploy your solution) as well as the Solution Finder Model, a problem-solving method which is based on the principle that in order to find a high quality solution, the 3 elements of need, objective and solution should always be identified and explicitly connected to build a coherent triad (the unity). This paper describes the eCiC approach, the method and models, the online tool as well as some applications in educational situations. As the eCiC system has already been used in distributed research teams, worldwide business companies and distant driven educational courses, a summary of experiences, possible applications and future developments will be made.

A software system for assessing the spatially distributed ecological risk posed by oil shipping

A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.

Why is Data Sharing in Collaborative Natural Resource Efforts so Hard and What can We Do to Improve it?

Increasingly, research and management in natural resource science rely on very large datasets compiled from multiple sources. While it is generally good to have more data, utilizing large, complex datasets has introduced challenges in data sharing, especially for collaborating researchers in disparate locations ("distributed research teams"). We surveyed natural resource scientists about common data-sharing problems. The major issues identified by our survey respondents (n=118) when providing data were lack of clarity in the data request (including format of data requested). When receiving data, survey respondents reported various insufficiencies in documentation describing the data (e.g., no data collection description/no protocol, data aggregated, or summarized without explanation). Since metadata, or "information about the data," is a central obstacle in efficient data handling, we suggest documenting metadata through data dictionaries, protocols, read-me files, explicit null value documentation, and process metadata as essential to any large-scale research program. We advocate for all researchers, but especially those involved in distributed teams to alleviate these problems with the use of several readily available communication strategies including the use of organizational charts to define roles, data flow diagrams to outline procedures and timelines, and data update cycles to guide data-handling expectations. In particular, we argue that distributed research teams magnify data-sharing challenges making data management training even more crucial for natural resource scientists. If natural resource scientists fail to overcome communication and metadata documentation issues, then negative data-sharing experiences will likely continue to undermine the success of many large-scale collaborative projects.

Using private blog sites to collect interobserver agreement and treatment integrity data.

single subject research places an emphasis on extended data collection for interobserver agreement and treatment integrity; however, distributed research teams make this effort difficult. if researchers live too far apart, the opportunity to collectively take data on interobserver agreement and treatment integrity poses a challenge. in this study, private blog sites were utilized to minimize travel distance and distributed research team variables during data collection practices. the use of private blog sites as a technological modality allowed video to be feasibly reviewed throughout the study (i.e., researchers viewed a video from home as opposed to, driving lengthy distances) while offering a superior option in contrast to traditional in vivo practices.

Social network analysis as a metric for the development of an interdisciplinary, inter-organizational research team

The development of an interdisciplinary and inter-organizational research team among eight of Canada’s leading emergency, geriatric medicine and rehabilitation researchers affiliated with six academic centers has provided an opportunity to study the development of a distributed team of interdisciplinary researchers using the methods of social network theory and analysis and to consider whether these methods are useful tools in the science of team science. Using traditional network analytic methods, the team of investigators were asked to rate their relationships with one another retrospectively at one year prior to the team’s first meeting and contemporaneously at two subsequent yearly intervals. Using network analytic statistics and visualizations the data collected finds an increase in network density and reciprocity of relationships together with more distributed centrality consistent with the findings of other researchers. These network development characteristics suggest that the distributed research team is developing as it should and supports the assertion that network analysis is a useful science of team science research tool.

An elastic virtual infrastructure for research applications (ELVIRA)

Cloud computing infrastructures provide a way for researchers to source the computational and storage resources they require to conduct their work and to collaborate within distributed research teams. We provide an overview of a cloud-based elastic virtual infrastructure for research applications that we have established to provide researchers with a collaborative research environment that automatically allocates cloud resources as required. We describe how we have used this infrastructure to support research on the Sun’s corona and how the elasticity provided by cloud infrastructures can be leveraged to provide high-throughput computing resources using a set of off-the-shelf technologies and a small number of additional tools that are simple to deploy and use. The resulting infrastructure has a number of advantages for the researchers compared to traditional clusters or grid computing environments that we discuss in the conclusions.

Research teams as complex systems: implications for knowledge management

The recent increase in research collaboration creates the need to better understand the interaction between individual researchers and the collaborative team. The paper elaborates the conceptualisation of research teams as complex systems which emerge out of the local interactions of individual members operating in their local research groups, and which exhibit different dynamics: the local, the global dynamics, and the contextual dynamics. A model of research teams as complex systems is also introduced. This conceptualisation provides unique insights on management of distributed research teams: (a) the internal operations of some teams are more sensitive to external events than others; (b) conflicts emerge as a mismatch of management structures at the different levels in which a team operates; and (c) teams of high complexity have additional coordination needs, which can be fulfilled by the use of information and communication technologies. Recommendations are drawn for the use of a complex adaptive systems model in the field of knowledge management.

Research productivity in the era of the internet revisited

In distributed research teams, internet is used for coordination, exchange of resources and sharing work, with the underlying assumption that internet use increases research productivity. The purpose of the article is to investigate this assumption in the context of two distributed research teams, with different coordination and management needs. The results suggest that the positive impact of internet use on research productivity is limited and may only be relevant only when collaborative endeavours suffer coordination problems. At the same time, meetings prove the most important predictor of research productivity. Implications are drawn for the management of distributed research teams.

Service‐oriented approach to collaborative visualization

AbstractThis paper presents a new service‐oriented approach to the design and implementation of visualization systems in a Grid computing environment. The approach evolves the traditional dataflow visualization system, based on processes communicating via shared memory or sockets, into an environment in which visualization Web services can be linked in a pipeline using the subscription and notification services available in Globus Toolkit 4. A specific aim of our design is to support collaborative visualization, allowing a geographically distributed research team to work collaboratively on visual analysis of data. A key feature of the system is the use of a formal description of the visualization pipeline, using the skML language first developed in the gViz e‐Science project. This description is shared by all collaborators in a session. In co‐operation with the e‐Viz project, we generate user interfaces for the visualization services automatically from the skML description. The new system is called notification‐service‐based collaborative visualization. A simple prototype has been built and is used to illustrate the concepts. Copyright © 2008 John Wiley & Sons, Ltd.

C-ME: A 3D Community-Based, Real-Time Collaboration Tool for Scientific Research and Training

The need for effective collaboration tools is growing as multidisciplinary proteome-wide projects and distributed research teams become more common. The resulting data is often quite disparate, stored in separate locations, and not contextually related. Collaborative Molecular Modeling Environment (C-ME) is an interactive community-based collaboration system that allows researchers to organize information, visualize data on a two-dimensional (2-D) or three-dimensional (3-D) basis, and share and manage that information with collaborators in real time. C-ME stores the information in industry-standard databases that are immediately accessible by appropriate permission within the computer network directory service or anonymously across the internet through the C-ME application or through a web browser. The system addresses two important aspects of collaboration: context and information management. C-ME allows a researcher to use a 3-D atomic structure model or a 2-D image as a contextual basis on which to attach and share annotations to specific atoms or molecules or to specific regions of a 2-D image. These annotations provide additional information about the atomic structure or image data that can then be evaluated, amended or added to by other project members.

The ITER CODAC conceptual design

CODAC orchestrates the activity of 60–90 Plant Systems in normal ITER operation. Interlock Systems protect ITER from potentially damaging operating off-normal conditions. Safety Systems protect the personnel and the environment and will be subject to licensing. The principal challenges to be met in the design and implementation of CODAC include: complexity, reliability, transparent access respecting security, a high experiment data rate and data volume since ITER is an experimental reactor, scientific exploitation from multiple Participant Team Experiment Sites and the long 35-year period for construction and operation. Complexity is addressed by prescribing the communication interfaces to the Plant Systems and prescribing the technical implementation within the Plant Systems. Plant Systems export to CODAC all the information on their construction and operation as “self-description”. Complexity is also addressed by automating the operation of ITER and of the plasma, using a structured data description of “Operation Schedules” which encompass all non-manual control, including Plasma Control. Reliability is addressed by maximising code reuse and maximising the use of existing products thereby minimising in-house development. The design is hierarchical and modular in both hardware and software. The latter facilitates evolution of methods during the project lifetime. Guaranteeing security while maximising access is addressed by flow separation. Out-flowing data, including experimental signals and the status of ITER plant is risk-free. In-flowing commands and data originate from Experiment Sites. The Cadarache Experiment Site is equated with the Remote Experiment Sites and a rigorous “Operation Request Gatekeeper” is provided. The high data rates and data volumes are handled with high performance networks. Global Area Networks allow Participant Teams to access all CODAC data and applications. Scientific exploitation of ITER will remain a human as well as technical challenge, to find methods of effectively combining the experience and observations of a geographically distributed research team.

Distributed Research Teams: Meeting Asynchronously in Virtual Space

As computer networks improve, more social and work interactions are carried out “virtually” by geographically separated group members. In this paper we discuss the design of a tool, PAVE, to support remote work interactions among colleagues in different time zones. PAVE extends a 2D graphical MOO and supports synchronous and asynchronous interactions. PAVE logs and indexes activities in the space. This capture facility enables playback and augmentation of meeting interactions by non-collocated group members. Thus, members can participate asynchronously in meetings they could not attend in real time, not just review them.

Resource Space Grid: model, method and platform

AbstractA Resource Space Grid is a virtual Grid that aims at effectively sharing, using and managing versatile resources across the Internet. The kernel of the Resource Space Grid includes a Resource Space Model (RSM) and a uniform Resource Using Mechanism (RUM). This paper presents the Resource Space Grid's core scientific issues and methodology, architecture, model and theory, design criteria and method, and practice. A normal form theory is proposed to normalize the resource space—a coordinate system for uniformly specifying and organizing resources. The RUM provides not only the end‐users with an operable resource browser to operate resources using the built‐in Resource Operation Language (ROL), but also the application developers with the ROL‐based programming environment. The prototype platform based on the proposed model and method has been implemented and used for sharing and managing resources in distributed research teams. Operations on Resource Spaces can constitute the virtual communities of Resource Space Grids—a platform independent resource sharing environment. Copyright © 2004 John Wiley & Sons, Ltd.