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Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility.

See RECORDING (starts at 00:30:30). In an attempt to increase the reproducibility of contributions to a long-running and established geospatial conference series, the 23rd AGILE Conference on Geographic Information Science 2020 (https://agile-online.org/conference-2020) for the first time provided guidelines on preparing reproducible papers (Nüst etal., 2020) and appointed a reproducibility committee to evaluate computational workflows of accepted papers ( https://www.agile-giscience-series.net/review_process.html). Here, the committee’s members report on the lessons learned from reviewing 23 accepted full papers and outline future plans for the conference series. In summary, six submissions were partially reproduced by reproducibility reviewers, whose reports are published openly on OSF ( https://osf.io/6k5fh/). These papers are promoted with badges on the proceedings’ website (https://agile-giss.copernicus.org/articles/1/index.html). Compared to previous years’ submissions (cf. Nüst etal. 2018), the guidelines and increased community awareness markedly improved reproducibility. However, the reproduction attempts also revealed problems, most importantly insufficient documentation. This was partly mitigated by the non-blind reproducibility review, conducted after paper acceptance, where interaction between reviewers and authors can provide the input and attention needed to increase reproducibility. However, the reviews also showed that anonymisation and public repositories, when properly documented, can enable a successful reproduction without interaction, as was the case with one manuscript. Individual and organisational challenges due to the COVID-19 pandemic and the conference’s eventual cancellation increased the teething problems. Nevertheless, also under normal circumstances, future iterations will have to reduce the reviewer’s efforts to be sustainable, ideally by more readily executable workflows and a larger reproducibility committee. Furthermore, we discuss changes to the reproducibility review process and their challenges. Reproducibility reports could be made available to “regular” reviewers, or the reports could be considered equally for acceptance/rejection decisions. Insufficient information or invalid arguments for not disclosing material could then lead to a submission being rejected or not being sent out to peer review. Further organisational improvements are a publication of reviewers’ activities in public databases, making the guidelines mandatory, and collecting data on used tools/repositories, spent efforts, and communications. Finally, we summarise the revision of the guidelines, including their new section for reproducibility reviewers, and the status of the initiative “Reproducible Publications at AGILE Conferences” (https://reproducible-agile.github.io/initiative/), which we connect to related undertakings such as CODECHECK (Eglen etal., 2019). The AGILE Conference’s experiences may help other communities to transition towards more open and reproducible research publications.

t-Testing is a common component of inferential statistics when comparing two means. This paper explains the central limit theorem and the concept of the null hypothesis as well as types of errors. On the practical side, this paper outlines how different t-tests may be performed in Microsoft Excel, for different purposes, both statically as well as dynamically, with Excel's functions.

Plotting data into graphs is a crucial step in data analysis as part of an initial descriptive statistics exercise since it gives the researcher an overview of the shape and nature of the data. Outlier values may also be identified, and these may be incorrect data, or true and important outliers. This paper explains how to access Microsoft Excel's Analysis Toolpak and provides some pointers for the utilisation of the histogram tool within the Toolpak.

Open source software (OSS) is a software product with the source code made public so that anyone can read, analyze, and change or improve the code. The use of this software is under a license, like Apache, GNU, MIT, Mozilla Public, and Eclipse Public License. Open source software development (OSSD) provides high quality assurance through user testing and peer reviews. The quality of these products depends on the size of the product community. This paper discusses the stakeholders of the OSS community, the quality assurance frameworks and models proposed in some studies, some statistics about OSS, the problems that affect the quality of OSSD, and the advantages and disadvantages of OSS compared to closed source software. This allows us to understand how we can achieve and improve the quality assurance and quality control of OSSD.

Peer reviews and feedback from colleagues give an author other opinions and suggestions to improve a scientific paper. To provide guidance for giving such feedback, this paper presents patterns on how to find, structure, and give feedback on scientific papers. Additionally this paper gives an overview of literature on reviewing scientific papers.

Peer reviews provide a time-honored way to give feedback and evaluate writing, yet few student papers receive this sort of scrutiny. This article examines qualitative and procedural reasons that ha...

The process of developing a publication guide titled “How to write your first academic paper” was presented in this paper. A detailed qualitative approach was followed to extract key elements from transaction and conference papers that appeared in the IEEE Transactions of Information Theory during the past decade. The approach taken was to learn from the experts, in this case IEEE Fellows and distill it into a step-by-step guide, conforming to a set of design principles. The publication guide was implemented at the Faculty of Engineering and many positive results achieved.

Peer reviewing is a central component in the scientific publishing process. We present the first public dataset of scientific peer reviews available for research purposes (PeerRead v1),1 providing an opportunity to study this important artifact. The dataset consists of 14.7K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR. The dataset also includes 10.7K textual peer reviews written by experts for a subset of the papers. We describe the data collection process and report interesting observed phenomena in the peer reviews. We also propose two novel NLP tasks based on this dataset and provide simple baseline models. In the first task, we show that simple models can predict whether a paper is accepted with up to 21% error reduction compared to the majority baseline. In the second task, we predict the numerical scores of review aspects and show that simple models can outperform the mean baseline for aspects with high variance such as ‘originality’ and ‘impact’.

Infections encompass a set of medical conditions of very diverse kinds that can pose a significant risk to health, and even death. As with many other diseases, early diagnosis can help to provide patients with proper care to minimize the damage produced by the disease, or to isolate them to avoid the risk of spread. In this context, computational intelligence can be useful to predict the risk of infection in patients, raising early alarms that can aid medical teams to respond as quick as possible. In this paper, we survey the state of the art on infection prediction using computer science by means of a systematic literature review. The objective is to find papers where computational intelligence is used to predict infections in patients using physiological data as features. We have posed one major research question along with nine specific subquestions. The whole review process is thoroughly described, and eight databases are considered which index most of the literature published in different scholarly formats. A total of 101 relevant documents have been found in the period comprised between 2003 and 2019, and a detailed study of these documents is carried out to classify the works and answer the research questions posed, resulting to our best knowledge in the most comprehensive study of its kind. We conclude that the most widely addressed infection is by far sepsis, followed by Clostridium difficile infection and surgical site infections. Most works use machine learning techniques, from which logistic regression, support vector machines, random forest and naive Bayes are the most common. Some machine learning works provide some ideas on the problems of small data and class imbalance, which can be of interest. The current systematic literature review shows that automatic diagnosis of infectious diseases using computational intelligence is well documented in the medical literature.

This paper studies electrical engineering learners’ preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called “slectures,” and some others. The results suggest that graduate students’ perception of the usefulness of the activity increases with its level of activity. For undergraduate students, an increased perception of the usefulness of the activity was observed for lightly active but structured learning methods. Group-based analysis focusing on two types of learners, defined as “instructor-dependent” and “instructor-independent” according to their perception of the usefulness of the classroom lectures, was also performed. The results suggest that instructor-independent learners may benefit more from active learning methods than instructor-dependent learners. For example, instructor-independent undergraduate learners were found to perceive the homework assignment as being more useful than the lectures. Such a preference was not seen in the average group data. In fact, no learning method was found to be perceived as more useful than the lectures, on average. Thus this paper illustrates the pertinence of group-based data analysis.

With a tremendous growth in the number of scientific papers, researchers have to spend too much time and struggle to find the appropriate papers they are looking for. Local citation recommendation that provides a list of references based on a text segment could alleviate the problem. Most existing local citation recommendation approaches concentrate on how to narrow the semantic difference between the scientific papers’ and citation context’s text content, completely neglecting other information. Inspired by the successful use of the encoder-decoder framework in machine translation, we develop an attention-based encoder-decoder (AED) model for local citation recommendation. The proposed AED model integrates venue information and author information in attention mechanism and learns relations between variable-length texts of the two text objects, i.e., citation contexts and scientific papers. Specifically, we first construct an encoder to represent a citation context as a vector in a low-dimensional space; after that, we construct an attention mechanism integrating venue information and author information and use RNN to construct a decoder, then we map the decoder’s output into a softmax layer, and score the scientific papers. Finally, we select papers which have high scores and generate a recommended reference paper list. We conduct experiments on the DBLP and ACL Anthology Network (AAN) datasets, and the results illustrate that the performance of the proposed approach is better than the other three state-of-the-art approaches.

Active learning and formative assessment techniques are the cutting edge of the modern education. This paper considers peer assessment automation and touches the topic of high actuality in advancing ICT for active learning. The roots of the study are obtained difficulties in adoption of the currently available peer assessment systems to engineering education introductory courses. The main goal of the paper is to collect software requirements and to build a peer assessment system, which may be easily agreed with standard educational routines (e.g. e-mailing) and which is be able to support complex artifacts interchange during a peer assessment session. The software requirements specification (SRS) for such a system has been created as a result of reviewing educational studies, technical reports and academic publications on common peer assessment processes and existing peer assessment systems. We also introduce the open source Mail-based Randomized Double-Blinded Peer-assessment System for Complex Artifacts called PASCA, which is developed according to this SRS and the results of PASCA adoption to an introductory programming course.

Individual research output (IRO) evaluation is a multi-criteria problem often conducted in groups. In practice, it is necessary to concurrently apply both bibliometric measures and peer review when evaluating the IRO. During the peer review process, different evaluators may use different linguistic terms because of individual differences in cognitive styles, and therefore, they may give ratings based on different assessing attitudes. Further, the weights between bibliometric measures and peer subjective judgments are difficult to determine. Motivated by these difficulties, this paper proposes a quantitative context-free grammar judgment description with an embedded assessing attitude. The proposed method quantitatively handles the assessing attitude and increases the flexibility of the linguistic information. Accordingly, this paper develops a multi-criteria group IRO evaluation method with context-free grammar judgments which concurrently considers bibliometric measures and peer review opinions. To overcome the weighting difficulties and achieve the maximum consensus, this paper proposes a distance-based method to determine the evaluators' weights and a weighted averaging operator to compute the criteria weights. After that, a TOPSIS-based aggregation method is applied to aggregate the objective and subjective ratings. A practical case study is then used to test the feasibility of the methodology. Finally, we discuss the effectiveness of the proposed method.

The nature of scientific research in mathematical and computational biology allows editors and reviewers to evaluate the findings of a scientific paper. Replication of a research study should be the minimum standard for judging its scientific claims and considering it for publication. This requires changes in the current peer review practice, and a strict adoption of a replication policy similar to those adopted in experimental fields such as organic synthesis. In the future, the culture of replication can be easily adopted by publishing papers through dynamic computational notebooks combining formatted text, equations, computer algebra and computer code.

Peer review holds a central place within the scientific communication system. Traditionally, research quality has been assessed by peer review of journal articles, conference proceedings, and books. There is strong support for the peer review process within the academic community, with scholars contributing peer reviews with little formal reward. Reviewing is seen as a contribution to the community as well as an opportunity to polish and refine understanding of the cutting edge of research. This paper discusses the applicability of the peer review process for assessing and ensuring the quality of datasets. Establishing the quality of datasets is a multifaceted task that encompasses many automated and manual processes. Adding research data into the publication and peer review queues will increase the stress on the scientific publishing system, but if done with forethought will also increase the trustworthiness and value of individual datasets, strengthen the findings based on cited datasets, and increase the transparency and traceability of data and publications. This paper discusses issues related to data peer review—in particular, the peer review processes, needs, and challenges related to the following scenarios: 1) data analyzed in traditional scientific articles, 2) data articles published in traditional scientific journals, 3) data submitted to open access data repositories, and 4) datasets published via articles in data journals.

Maintain quality is always an important issue for the software end product. This paper includes how to improve quality of product by detecting possible number of defects potentials. The authors are using an approach called Peer Review for detection of defect potential. In this paper peer review is done using an agile approach. A study has been conducted on three final year projects and includes the detection of maximum number of defect potentials using different peer review techniques. Finally, as a result, total numbers of defects with different review techniques are compared with possible defects.

Source: doi: 10.1109/ACCESS.2016.2599851 Collecting data via a questionnaire and analyzing them while preserving respondents' privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy- preserving method for collecting and analyzing survey responses using secure multi-party computation. The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire data set of 3158 respondents sampled for a medical study and simulated questionnaire data sets of up to 50 000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.

Dear editor The peer review system relies on assessment of ingenious work by other people in the same domain in order to preserve or improve the quality and creativity of the work.1 Discussion and suggestions on improving the reliability of the process are made in this letter. Peer review is like a gatekeeper in the academic world, and the methods for putting peer review into practice vary across journals and disciplines. The theory behind this system is that a larger and more diverse group of people will usually find more flaws in a work and will be able to make a more unbiased assessment of it than just the person or group who created the work. The strength and weaknesses of the peer review process have been discussed by Sollenberger in a review article.2 Peer review utilizes self-governance and the anonymity of the reviewers (referees) so as to discourage cronyism (ie, bias shown to family and friends) and obtain an unbiased report. The reviewers are not selected from amongst the close colleagues/relatives/friends of the author. The procedure of peer review is shown in Figure 1. Specialists in a given field judge the professional performance, creativity, or quality of scientific work produced by others in their field or area of competence. In single-blind review, the reviewer identity is hidden to encourage unbiased comments, while in double-blind review, the author’s identity is masked from reviewers to shield against forms of social bias. Further, an “open peer” review journal may employ a “third” party, ie, someone who is neither affiliated directly with the reviewing entity nor associated with author being reviewed. Figure 1 Procedure of peer review. There can also be a system of postpublication open-review comments, normally mediated by the editor, that can be posted by readers and reviewers after the article has been published. The scientific community is in search of ways to make peer review more efficient and effective. It is essential to maintain standards whilst also reducing the load on the reviewers (who are doing honorary work mostly). The process of peer review has evolved away from hard copy to a fully integrated online process, and all major journals usually accept online submissions. Thus peer review has become quicker and with a far lower administrative burden. But there is still plenty of room for improvement within the current peer review process. Editors are made, not born, and good team work along with technological support can help them do a better job.3 Thus reviewers and editors should be trained to adapt with the evolution in scientific publishing, and be aware that all digital pictures should mandatorily have attached metadata and embossed watermark.4 As recommended by Jolly,5 in addition, each paper can be allocated a “guardian”, who is a member of the editorial board particularly accountable for ensuring the satisfactoriness of the peer review process and providing an extra viewpoint regarding the quality of the paper. Papers should only be accepted for publication after authors have aptly addressed the queries raised by the authority (referees/guardians/editor/editorial board). Thus, in addition to peer review, multiple-point quality checks in the review process are implemented by the editor and editorial board. Another recommendation is adaptation of appropriate ethical policies, regulation, and best practice. Authors, reviewers, and editors will be required to read and adhere to these policies, which reflect the high standards we expect in peer review. A number of organizations (such as the International Committee of Medical Journal Editors and Committee on Publication Ethics) describe these policies for the peer review process.

This paper reports on two controlled experiments comparing pair programming with single developers who are assisted by an additional anonymous peer code review phase. The experiments were conducted in the summer semester 2002 and 2003 at the University of Karlsruhe with 38 computer science students. Instead of comparing pair programming to solo programming this study aims at finding a technique by which a single developer produces similar program quality as programmer pairs do but with moderate cost. The study has one major finding concerning the cost of the two development methods. Single developers are as costly as programmer pairs, if both programmer pairs and single developers with an additional review phase are forced to produce programs of similar level of correctness. In conclusion, programmer pairs and single developers become interchangeable in terms of development cost. As this paper reports on the results of small development tasks the comparison could not take into account long time benefits of either technique.

For more than 20 years, the German Workshop on Medical Image Processing (Bildverarbeitung fur die Medizin, BVM) is held annually and has been established recently as a European conference. In 2010, the workshop was held in Aachen, Germany. Based on a double-blind review process with at least three experts reviewing each manuscript, the best 20 papers have been invited contributing to this special issue. The thirteen submissions received have passed an international peer review process. Finally, eleven papers have been accepted for publication. This includes two invited papers by Scholl et al. and Wismueller.

Message From The Guest Editors Dear Readers It is the great honor for us to edit this special issue of AWERProcedia Information Technology and Computer Science Journal for the selected revised papers presented in the 2nd World Conference on Information Technology (WCIT-2011) held on November 23-27, 2011, at the Queen Elizabeth Elite Suits and Hotel in historical and touristic city of Antalya in Turkey. As the guest editors of this issue, we are glad to see variety of articles focusing on the major topics of the information technology: Algorithms, artificial intelligence, biometrics, biosensors, cellular, automata, computer architecture, computer graphics, computing methodologies, data mining, data warehouse and applications, database systems, decision support systems, digital ecosystems, digital forensics, distance learning, distributed learning environments, e-business, e-commerce, educational applications, educational software, educational technologies, educational computing, e-government, e-marketing, e-publishing, expert systems, fuzzy logic, genetic algorithms & programming, hardware design, human computer interaction, human tracking technologies, industrial applications, information policy making, information retrieval systems, information systems engineering, information technology & agriculture, information technology & arts and design, information technology & commerce, information technology & health, information technology & languages, intelligent and fuzzy information processing, intelligent tutoring systems, interactive learning environments, internet applications, internet security, knowledge engineering, knowledge management, learning management systems, medical informatics, mobile computing, mobile devices, mobile learning, multimedia applications, networked tools, parallel computing, programming languages, remote laboratories/e-lab, social computing, software/distributed systems, software engineering, sport applications, tele-learning, video conferencing, wearable computing, web based language development, web services, wireless and ad-hoc networks and etc. Scholars from all over the world contributed to this issue of the journal. Special thanks are to all the reviewers, the members of the international editorial board, the publisher, and those involved intechnical processes. We would like to thanks all who contributed to in every process to make this issue actualized. A total of 849 abstracts or full papers were submitted for this issue and each paper has been peer reviewed by the reviewers specialized in the related field. At the end of the review process, a total of 274 high quality research papers were selected and accepted for publication. We hope that you will enjoy reading the papers. Best regards Prof. Dr. Hafize Keser Ankara University, Turkey hafizekeser@yahoo.com.tr Sezer Kanbul, M.Sc. Near East University, North Cyprus sezerkanbul@yahoo.com

Peer-review systems such as SWoRD lack intelligence for detecting and responding to problems with students’ reviewing performance. While prior work has demonstrated the feasibility of automatically identifying desirable feedback features in free-text reviews of student papers, similar methods have not yet been developed for feedback regarding argument diagrams. One desirable feedback feature is problem localization, which has been shown to positively correlate with feedback implementation in both student papers and argument diagrams. In this paper we demonstrate that features previously developed for identifying localization in paper reviews do not work well when applied to peer reviews of argument diagrams. We develop a novel algorithm tailored for reviews of argument diagrams, and demonstrate significant performance improvements in identifying problem localization in an experimental evaluation.

Understanding the peer review process could help research and shed light on the mechanisms that underlie crowdsourcing. In this paper, we present an agent-based model of peer review built on three entities - the paper, the scientist and the conference. The system is implemented on a BDI platform (Jason) that allows to define a rich model of scoring, evaluating and selecting papers for conferences. Then, we propose a programme committee update mechanism based on disagreement control that is able to remove reviewers applying a strategy aimed to prevent papers better than their own to be accepted (rational cheating). We analyze a homogeneous scenario, where all conferences aim to the same level of quality, and a heterogeneous scenario, in which conferences request different qualities, showing how this affects the update mechanism proposed. We also present a first step toward an empirical validation of our model that compares the amount of disagreements found in real conferences with that obtained in our simulations. © 2013 World Scientific Publishing Company.

In this paper we present an experimental environment of 3D books combined with a game application that has been developed by a collaboration project between the Norwegian University of Science and Technology in Trondheim, Norway the NTNU University Library, and the Percro laboratory of Santa Anna University in Pisa, Italy. MUBIL is an international research project involving museums, libraries and ICT academy partners aiming to develop a consistent methodology enabling the use of Virtual Environments as a metaphor to present manuscripts content through the paradigms of interaction and immersion, evaluating different possible alternatives. This paper presents the results of the application of two prototypes of books augmented with the use of XVR and IL technology. We explore immersive-reality design strategies in archive and library contexts for attracting new users. Our newly established Mubil-lab has invited school classes to test the books augmented with 3D models and other multimedia content in order to investigate whether the immersion in such environments can create wider engagement and support learning. The metaphor of 3D books and game designs in a combination allows the digital books to be handled through a tactile experience and substitute the physical browsing. In this paper we present some preliminary results about the enrichment of the user experience in such environment. © Author(s) 2013. This work is distributed under the Creative Commons Attribution 3.0 License.

This paper deals with managing the peer review process with an electronic management system (EMS). Our approach uses a WWW-based interface to an Oracle database. We describe different aspects of the EMS, namely the peer review process, report generation, and security. An experimental peer review system was developed for the Fourth International World Wide Web (WWW) Conference, which provided a model to automate the underlying processes that had been driven primarily by pen and paper. This system uses the very technology that the International WWW Conference Committee (IW3C2) promotes, so it is fitting that the conference be automated with a WWW-based system. The experimental system has evolved with the help of many suggestions to provide better support for the WWW5 conference as well. This paper discusses the first experimental system, some lessons learned, and the second more evolved system for the WWW5 conference with emphasis on the latter.

Peer review expert selection is an important link of fund project review; it can not only improve the matching accuracy of domain experts and projects, but also improve the appraisal quality in fund project review. This paper mainly studies the peer review expert selection method in fund project review. With the actual experience of fund project management, based on the author's knowledge set theory, paper analyzes deeply knowledge set representation of expert knowledge, improves the similarity calculation of expert and project knowledge, builds the peer review expert selection method, and gives the actual example.

In this paper we present a study where a peer reviewing system targeted for conference paper evaluation has been used for enhancing the learning of programming though peer review. For peer reviewing purposes two open source systems were evaluated and MyReview was selected for evaluation. The peer review system was used in one programming focused course and the benefits of peer reviewing were analyzed from the reviewer and reviewee point of view. The results show that a peer review system targeted for conference paper evaluations is applicable for reviewing programs although the system should be much simpler. Students appreciated the documented comments from other students but were more interested in lecturer or other expert opinion.

The review cycle for papers takes way too long in many disciplines. The problem is that while authors want to have their own papers reviewed fast, that are often unwilling to review the papers of others in a timely manner. This paper explores what would be required to incentivize fast reviews using a public reputation/scoring system that exploits the fact that the referees are drawn from the same pool as paper authors. The challenge in maintaining a public reputation system is to ensure that the identity of referees remain as anonymous as possible. A model is proposed in this work, wherein authors have an incentive to commit to reviewing papers and are rewarded for meeting this commitment in a manner that prioritizes their own papers for reviews. This ensures stability (bounded reviewing delays) for all fair contributors while freeloaders face a potentially unstable system. A naive implementation of the scoring system, however, leaks information that would allow authors to infer the likely identities of their referees. A distortion to the observed public score process is then studied, which is shown to enhance anonymity while preserving the incentives for timely refereeing.

This paper proposes that experience knowledge would be beneficial for iterative software development. In this paper, experience knowledge- based artifacts have been linked to Extreme Programming via peer reviews. Experience knowledge can be defined as human experiences documented with the object of exploiting them in the organization. Extreme Programming has been selected to represent iterative software development processes. Systematically gathering experiences would support building evidence for improving and teaching iterative software development processes. This paper presents one possible solution as to how to put experience knowledge in practice in the context of iterative software development processes. It also reports results from projects where experience knowledge has been studied. The main findings of this paper are two ways in which experience knowledge- based artifacts can be used with iterative software development, and that peer reviews are a good way to collect and treat experience knowledge-based artifacts.

Autonomous underwater vehicles (AUVs) are efficient sensor-carrying platforms for mapping and monitoring undersea ice. However, under-ice operations impose demanding requirements to the system, as it must deal with uncertain and unstructured environments, harsh environmental conditions, and reduced capabilities of the navigational sensors. This paper proposes a Bayesian approach to supervisory risk control, with the objective of providing risk management capabilities to the control system. First, an altitude guidance law for following a contour of an ice surface via pitch control using measurements from a Doppler velocity log (DVL) is proposed. Furthermore, a Bayesian network (BN) for probabilistic reasoning over the current state of risk during the operation is developed. This is then extended to a decision network (DN) for autonomously adapting the behavior of the AUV in order to maximize the mission utility, subject to a constraint on the predicted risk from the risk model. The vehicle is thus able to autonomously adapt its behavior in response to its current belief about the risk. The goal of this work is to improve the AUV performance and likelihood of mission success. Results from a simulation study are presented in order to demonstrate the performance of the proposed method.

Zlto(zlah-toh) is a project to provide secure validation of credentials for young people. Many African youth find it difficult to obtain jobs because of a lack of formal qualification, but they have a breath of informal skills. In this paper we will describe how we implement the Zlto system to provide proof of skills completed through a peer-to-peer evaluation mechanism and stored using blockchain. Since its first deployment in 2016, Zlto has processed over 1 million transactions. We present simulation and analysis of the reputation protocol used to verify work, and further evaluate the peer review process using a think a loud focus group method with a group of peer reviewers in order to improve the system.

We present an annotation approach to capturing emotional and cognitive empathy in student-written peer reviews on business models in German. We propose an annotation scheme that allows us to model emotional and cognitive empathy scores based on three types of review components. Also, we conducted an annotation study with three annotators based on 92 student essays to evaluate our annotation scheme. The obtained inter-rater agreement of {\alpha}=0.79 for the components and the multi-{\pi}=0.41 for the empathy scores indicate that the proposed annotation scheme successfully guides annotators to a substantial to moderate agreement. Moreover, we trained predictive models to detect the annotated empathy structures and embedded them in an adaptive writing support system for students to receive individual empathy feedback independent of an instructor, time, and location. We evaluated our tool in a peer learning exercise with 58 students and found promising results for perceived empathy skill learning, perceived feedback accuracy, and intention to use. Finally, we present our freely available corpus of 500 empathy-annotated, student-written peer reviews on business models and our annotation guidelines to encourage future research on the design and development of empathy support systems., Comment: to be published in The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)

Simulation models have proven to be valuable tools for studying peer review processes. However, the effects of some of these models’ assumptions have not been tested, nor have these models been examined in comparative contexts. In this paper, we address two of these assumptions which go in tandem: (1) on the granularity of the evaluation scale, and (2) on the homogeneity of the grade language (i.e. whether reviewers interpret evaluation grades in the same fashion). We test the consequences of these assumptions by extending a well-known agent-based model of author and reviewer behaviour with discrete evaluation scales and reviewers’ interpretation of the grade language. In this way, we compare a peer review model with a homogeneous grade language, as assumed in most models of peer review, with a more psychologically realistic model where reviewers interpret the grades of the evaluation scale heterogeneously. We find that grade language heterogeneity can indeed affect the predictions of a model of peer review. Science Foundation Ireland

The Graph Query Language (GraphQL) is a framework for de- veloping Web Services, which works on the domain model level rather than the functions. While the declarative nature of this framework has already attracted the interest of practitioners in both academia and industry, it still lacks integration capabilities. This shortcoming has been recognized in the industry; there exists a first tool creating a federation—a virtual integrated system—on top of instrumented systems. Being relatively new, it suffers from a few practical and conceptual shortcomings, such as consolidation of (conflicting) schemas and identification of multiple types. In this paper, we will analyze the federation challenge and propose a solution utilizing multi-view modeling and domain specific modeling. Our approach is accom- panied by a proof-of-concept implementation and provides a model-based presentation of the GraphQL framework.

The megajournal is a new form of an academic open-access journal that is peer reviewed for scientific and methodological soundness. Thus, the perceived importance is not assessed, leaving it to the readers to decide whether an article is of interest and importance to them. After the highly successful launch of the PLOS ONE megajournal, other publishers followed this path. The current paper undertakes a review of the articles published internationally on the megajournal criteria defining its concept. It also traces how the new type of scientific publication has been developing and expanding since the PLoS ONE launch in 2006.