Boundary Spanning and Engineering: A Qualitative Systematic Review

Background

Engineers are often expected to span organizational, cultural, stakeholder, geographic, temporal, and other boundaries. Yet, few studies on boundary spanning have appeared in the engineering education literature, suggesting the need for improved theoretical and conceptual foundations to guide empirical studies of boundary spanning in engineering.

Purpose

To develop a more comprehensive understanding of boundary spanning, this study addresses five research questions: (a) What types of boundaries have been identified as topics of interest? (b) How are boundary spanners and boundary spanning defined? (c) What types of activities and behaviors comprise or have been linked to boundary spanning? (d) What individual competencies and characteristics have been proposed or studied as important for boundary spanning? and (e) What boundary spanning themes are most prominent in studies of engineers and other technical professionals?

Scope/Method

Using a qualitative systematic review process, we identified and analyzed 72 scholarly papers from multiple disciplines. Multiple reviewers coded each paper using a hybrid deductive‐inductive content analysis process to identify key themes related to boundary spanning.

Conclusions

The analysis resulted in a framework consisting of six boundary types, three types of roles and definitions, and five types of activities. Discussion of boundary spanning competencies was limited in the collected works, and only seven papers exclusively focused on engineers. We conclude by proposing boundary spanning as an important meta‐attribute for engineers and a promising lens for investigating engineering practice. We also relate our findings to the engineering education literature and suggest directions for future research.     

Virtual worlds as knowledge management platform – a practice‐perspective

Virtual worlds, as electronic environments where individuals can interact in a realistic manner in form of avatars, are increasingly used by gamers, consumers and employees. Therefore, they provide opportunities for reinventing business processes. Especially, effective knowledge management (KM) requires the use of appropriate information and communication technology (ICT) as well as social interaction. Emerging virtual worlds enable new ways to support knowledge and knowing processes because these virtual environments consider social aspects that are necessary for knowledge creating and knowledge sharing processes. Thus, collaboration in virtual worlds resembles real‐life activities. In this paper, we shed light on the use of Second Life (SL) as a KM platform in a real‐life setting. To explore the potential and current usage of virtual worlds for knowledge and knowing activities, we conducted a qualitative study at IBM. We interviewed IBM employees belonging to a special workgroup called ‘Web 2.0/virtual worlds’ in order to gain experience in generating and exchanging knowledge by virtually collaborating and interacting. Our results show that virtual worlds – if they are able to overcome problems like platform stability, user interface or security issues – bear the potential to serve as a KM platform. They facilitate global and simultaneous interaction, create a common context for collaboration, combine different tools for communication and enhance knowledge and knowing processes.     

A proposal for student modeling based on ontologies and diagnosis rules

The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.     

A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS

Investigating the temporal and spatial pattern of landscape disturbances is an important requirement for modeling ecosystem characteristics, including understanding changes in the terrestrial carbon cycle or mapping the quality and abundance of wildlife habitats. Data from the Landsat series of satellites have been successfully applied to map a range of biophysical vegetation parameters at a 30 m spatial resolution; the Landsat 16 day revisit cycle, however, which is often extended due to cloud cover, can be a major obstacle for monitoring short term disturbances and changes in vegetation characteristics through time.The development of data fusion techniques has helped to improve the temporal resolution of fine spatial resolution data by blending observations from sensors with differing spatial and temporal characteristics. This study introduces a new data fusion model for producing synthetic imagery and the detection of changes termed Spatial Temporal Adaptive Algorithm for mapping Reflectance Change (STAARCH). The algorithm is designed to detect changes in reflectance, denoting disturbance, using Tasseled Cap transformations of both Landsat TM/ETM and MODIS reflectance data. The algorithm has been tested over a 185 × 185 km study area in west-central Alberta, Canada. Results show that STAARCH was able to identify spatial and temporal changes in the landscape with a high level of detail. The spatial accuracy of the disturbed area was 93% when compared to the validation data set, while temporal changes in the landscape were correctly estimated for 87% to 89% of instances for the total disturbed area. The change sequence derived from STAARCH was also used to produce synthetic Landsat images for the study period for each available date of MODIS imagery. Comparison to existing Landsat observations showed that the change sequence derived from STAARCH helped to improve the prediction results when compared to previously published data fusion techniques.     

Ahead of time static analysis for automatic generation of debugging interfaces to the Linux kernel

The Linux kernel does not export a stable, well-defined kernel interface, complicating the development of kernel-level services, such as device drivers and file systems. While there does exist a set of functions that are exported to external modules, this set of functions frequently changes, and the functions have implicit, ill-documented preconditions. No specific debugging support is provided. We present Diagnosys, an approach to automatically constructing a debugging interface for the Linux kernel. First, a designated kernel maintainer uses Diagnosys to identify constraints on the use of the exported functions. Based on this information, developers of kernel services can then use Diagnosys to generate a debugging interface specialized to their code. When a service including this interface is tested, it records information about potential problems. This information is preserved following a kernel crash or hang. Our experiments show that the generated debugging interface provides useful log information and incurs a low performance penalty.     

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.     

Knowledge transfer in globally distributed teams: the role of transactive memory

This paper explores the role of transactive memory in enabling knowledge transfer between globally distributed teams. While the information systems literature has recently acknowledged the role transactive memory plays in improving knowledge processes and performance in colocated teams, little is known about its contribution to distributed teams. To contribute to filling this gap, knowledge‐transfer challenges and processes between onsite and offshore teams were studied at TATA Consultancy Services. In particular, the paper describes the transfer of knowledge between onsite and offshore teams through encoding, storing and retrieving processes. An in‐depth case study of globally distributed software development projects was carried out, and a qualitative, interpretive approach was adopted. The analysis of the case suggests that in order to overcome differences derived from the local contexts of the onsite and offshore teams (e.g. different work routines, methodologies and skills), some specific mechanisms supporting the development of codified and personalized ‘directories’ were introduced. These include the standardization of templates and methodologies across the remote sites as well as frequent teleconferencing sessions and occasional short visits. These mechanisms contributed to the development of the notion of ‘who knows what’ across onsite and offshore teams despite the challenges associated with globally distributed teams, and supported the transfer of knowledge between onsite and offshore teams. The paper concludes by offering theoretical and practical implications.     

High-Energy Physics on the Grid: the ATLAS and CMS Experience

In this paper we present the experience of the ATLAS and CMS High-Energy Physics (HEP) experiments at the Large Hadron Collider (LHC) with the LCG/EGEE Grid infrastructure. The activity developed around the following two main lines: large-scale physics and detector simulations and end-user analysis. The LCG/EGEE Grid infrastructure offers a large amount of computing and storage resources and is growing very rapidly. It provides the natural environment for large-scale physics and detector simulations. Also, the analysis of these detector simulation data (and in the near future of the reconstructed data from physics collisions) requires efficient end-users access to Grid resources. In this paper, the main findings and lessons learned in terms of performance, robustness and scalability of the whole system are discussed in detail.     

The influence of lift frequency, lift duration and work experience on discomfort reporting

Discomfort surveys are commonly used to assess risk in the workplace and prioritize jobs for interventions before an injury or illness occurs. However, discomfort is a subjective measure and the relationship of discomfort to work-related factors is poorly understood. The objective of this study was to understand how reports of discomfort relate to work-related risk factors for the low back. A total of 12 novice and 12 experienced manual materials handlers performed repetitive, asymmetric lifts at different load levels and at six different lift frequencies throughout an 8-h exposure period. Discomfort was recorded hourly throughout the day. Analyses were performed to determine which experimental factors influenced reporting of discomfort and if discomfort trends matched spine loading trends. Novice lifters reported significantly higher discomfort levels than experienced subjects. They also reported increases in discomfort as moment exposure increased and as the exposure time increased. Novices lifting at 8 Nm load moment level reported increased discomfort from 0.07 to 0.63 by the end of the day, at 36 Nm they reported an increase from 0.04 to 0.40 and at 85 Nm they reported an increase from 0.37 to 3.06. Experienced subjects, on the other hand, reported low levels of discomfort regardless of moment exposure, lift frequency or exposure duration. The reported discomforts were generally unrelated to the biomechanical loading on the spine. Discomfort reporting appears to be more a reflection of experience than of work risk factor exposure. Experienced subjects may have more efficient motor patterns, which reduce spinal load and thus discomfort. Novice subjects seemed to have a lower threshold of discomfort. Caution is needed when using discomfort reporting as a means to identify jobs in need of interventions, in that biomechanical loading may not be accurately represented. Discomfort should only be used as a supplement to objective measures, such as spinal loading, to assess the risk of low back disorders.