A Framework for collaborative writing with recording and post-meeting retrieval capabilities

From a HCI perspective, elucidating and supporting the context in which collaboration takes place is key to implementing successful collaborative systems. Synchronous collaborative writing usually takes place in contexts involving a “meeting” of some sort. Collaborative writing meetings can be face-to-face or, increasingly, remote Internet-based meetings. The latter presents software developers with the possibility of incorporating multimedia recording and information retrieval capabilities into the collaborative environment. The collaborative writing that ensues can be seen as an activity encompassing asynchronous as well as synchronous aspects. In order for revisions, information retrieval and other forms of post-meeting, asynchronous work to be effectively supported, the synchronous collaborative editor must be able to appropriately detect and record meeting metadata. This paper presents a collaborative editor that supports recording of user actions and explicit metadata production. Design and technical implications of introducing such capabilities are discussed with respect to document segmentation, consistency control, and awareness mechanisms

Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

Strategies and challenges to facilitate situated learning in virtual worlds post-Second Life

Virtual worlds can establish a stimulating environment to support a situated learning approach in which students simulate a task within a safe environment. While in previous years Second Life played a major role in providing such a virtual environment, there are now more and more alternative—often OpenSim-based—solutions deployed within the educational community. By drawing parallels to social networks, we discuss two aspects: how to link individually hosted virtual worlds together in order to implement context for immersion and how to identify and avoid “fake” avatars so people behind these avatars can be held accountable for their actions

A Study of Implementation Methodologies for Distributed Real Time Collaboration

Collaboration drives our world and is almost unavoidable in the programming industry. From higher education to the top technological companies, people are working together to drive discovery and innovation. Software engineers must work with their peers to accomplish goals daily in their workplace. When working with others there are a variety of tools to choose from such as Google Docs, Google Colab and Overleaf. Each of the aforementioned collaborative tools utilizes the Operational Transform (OT) technique in order to implement their real time collaboration functionality. Operational transform is the technique seen amongst most if not all major collaborative tools in our industry today. However, there is another way of implementing real time collaboration through a data structure called Conflict-free Replicated Data Type (CRDT) which has made claims of superiority over OT. Previous studies have taken place with the focus on comparing the theory behind OT and CRDT\u27s, but as far as we know, there have not been studies which compare real time collaboration performance using an OT implementation versus a CRDT implementation in a popularly used product such as Google Docs or Overleaf. Our work will focus on comparing OT and CRDT\u27s real time collaborative performance in Overleaf, an academic authorship tool, which allows for easy collaboration on academic and professional papers. Overleaf\u27s current published version implements real time collaboration using operational transform. This thesis will contribute an analysis of the current real time collaboration performance of operational transform in Overleaf, an implementation of CRDT\u27s for real time collaboration in Overleaf and an analysis of the performance of real time collaboration through the CRDT implementation in Overleaf. This thesis describes the main advantages and disadvantages of OT vs CRDTs, as well as, to our knowledge, the first results of a non-theoretical attempt at implementing CRDTs for handling document edits in a collaborative environment which was originally operating using an OT implementation

Symbolic Model-Checking of Optimistic Replication Algorithms

The original publication is available at www.springerlink.comInternational audienceThe Operational Transformation (OT) approach, used in many collaborative editors, allows a group of users to concurrently update replicas of a shared object and exchange their updates in any order. The basic idea of this approach is to transform any received update operation before its execution on a replica of the object. This transformation aims to ensure the convergence of the different replicas of the object. However, designing transformation algorithms for achieving convergence is a critical and challenging issue. In this paper, we address the verification of OT algorithms with a symbolic model-checking technique. We show how to use the difference bound matrices to explore symbolically infinite state-spaces of such systems and provide symbolic counterexamples for the convergence property

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor