Interoperability between OPC UA and oneM2M

A key requirement of realizing the connected world featured by IoT is to ensure interoperability among different connected devices. Interoperability is also at the basis of the realization of the novel vision of Industry 4.0; a lot effort is put to make interoperable the interchange of information between industrial applications, also including IoT ecosystems. For this reason, during these last years, several approaches aimed to enhance interoperability between industrial applications and IoT appeared in the literature. In this paper an interoperability proposal is presented. It is based on the idea to realize interworking between the two standards considered among the reference ones in the industrial and IoT domains. They are the OPC UA for the industrial domain and oneM2M for the IoT. Interworking is realized in such a way to allow industrial applications based on OPC UA to acquire information coming from oneM2M-based IoT devices. The proposal allows an OPC UA Server to publish each piece of information produced by oneM2M-based IoT devices, so that this information may be consumed by industrial applications playing the OPC UA Client role.

Self-adaptive architectures in IoT systems: a systematic literature review

Over the past few years, the relevance of the Internet of Things (IoT) has grown significantly and is now a key component of many industrial processes and even a transparent participant in various activities performed in our daily life. IoT systems are subjected to changes in the dynamic environments they operate in. These changes (e.g. variations in bandwidth consumption or new devices joining/leaving) may impact the Quality of Service (QoS) of the IoT system. A number of self-adaptation strategies for IoT architectures to better deal with these changes have been proposed in the literature. Nevertheless, they focus on isolated types of changes. We lack a comprehensive view of the trade-offs of each proposal and how they could be combined to cope with simultaneous events of different types.In this paper, we identify, analyze, and interpret relevant studies related to IoT adaptation and develop a comprehensive and holistic view of the interplay of different dynamic events, their consequences on QoS, and the alternatives for the adaptation. To do so, we have conducted a systematic literature review of existing scientific proposals and defined a research agenda for the near future based on the findings and weaknesses identified in the literature.

Timed protocol analysis of interconnected mobile IoT devices

With the emergence of the Internet of Things (IoT), application developers can rely on a variety of protocols and Application Programming Interfaces (APIs) to support data exchange between IoT devices. However, this may result in highly heterogeneous IoT interactions in terms of both functional and non-functional semantics. To map between heterogeneous functional semantics, middleware connectors can be utilized to interconnect IoT devices via bridging mechanisms. In this paper, we make use of the Data eXchange (DeX) connector model that enables interoperability among heterogeneous IoT devices. DeX interactions, including synchronous, asynchronous and streaming, rely on generic post and get primitives to represent IoT device behaviors with varying space/time coupling. Nevertheless, non-functional time semantics of IoT interactions such as data availability/validity, intermittent connectivity and application processing time, can severely affect response times and success rates of DeX interactions. We introduce timing parameters for time semantics to enhance the DeX API. The new DeX API enables the mapping of both functional and time semantics of DeX interactions. By precisely studying these timing parameters using timed automata models, we verify conditions for successful interactions with DeX connectors. Furthermore, we statistically analyze through simulations the effect of varying timing parameters to ensure higher probabilities of successful interactions. Simulation experiments are compared with experiments run on the DeX Mediators (DeXM) framework to evaluate the accuracy of the results. This work can provide application developers with precise design time information when setting these timing parameters in order to ensure accurate runtime behavior.

An open source library to parse and analyze online collaborative knowledge-building portals

With the success of collaborative knowledge-building portals, such as Wikipedia, Stack Overflow, Quora, and GitHub, a class of researchers is driven towards understanding the dynamics of knowledge building on these portals. Even though collaborative knowledge building portals are known to be better than expert-driven knowledge repositories, limited research has been performed to understand the knowledge building dynamics in the former. This is mainly due to two reasons; first, unavailability of the standard data representation format, second, lack of proper tools and libraries to analyze the knowledge building dynamics.We describe Knowledge Data Analysis and Processing Platform (KDAP), a programming toolkit that is easy to use and provides high-level operations for analysis of knowledge data. We propose Knowledge Markup Language (Knol-ML), a generic representation format for the data of collaborative knowledge building portals. KDAP can process the massive data of crowdsourced portals like Wikipedia and Stack Overflow efficiently. As a part of this toolkit, a data-dump of various collaborative knowledge building portals is published in Knol-ML format. The combination of Knol-ML and the proposed open-source library will help the knowledge building community to perform benchmark analysis.Link of the repository: Verma et al. (2020)Video Tutorial: Verma et al. (2020)Supplementary Material: Verma et al. (2020)

The Wikipedia Diversity Observatory: helping communities to bridge content gaps through interactive interfaces

In this paper, we present the Wikipedia Diversity Observatory, a project aimed to increase diversity within Wikipedia content. The project provides dashboards with visualizations and tools which show content gaps in terms of imbalances in the coverage of topics, and of concepts that are not shared across Wikipedia language editions. The dashboards are built on datasets generated for each of the more than 300 existing language editions, with features that label each article according to geography, gender and other categories relevant to overall content diversity. Through various examples, we show how the tools encourage and help editors to bridge the gaps in Wikipedia content. Finally, we discuss the project’s impact on the communities and implications for the Wikimedia movement in a moment in which covering diversity is considered strategic.

Deployment of a LoRaWAN network and evaluation of tracking devices in the context of smart cities

Recent public cooperation between the Federal University of Technology – Parana (UTFPR) and the Toledo Municipality plans to implement the concept of smart cities in this city. In this context, one of the applications under development intends to track the recyclable garbage collector trucks in real time over the Internet. Actually, fleet vehicle tracking is one of the main applications for smart cities. LoRaWAN stands out among network technologies for smart cities due to operating in an open frequency range, covering long distances with low power consumption and low equipment cost. However, the coverage and performance of LoRaWAN is directly affected by both the environment and configuration parameters. In addition, tracking devices must be able to send its coordinates to the Internet even when the vehicle goes through zones where there are obstacles for electromagnetic waves such as elevated buildings or valleys. In this paper we perform experimental investigations to evaluate four LoRaWAN tracking devices, two available out of the box and two assembled and programmed. The behavior of each tracking device is analyzed when moving at a constant speed through three representative urban areas totaling 10.71 km2. The two most efficient tracking devices are analyzed in a stretch of 3.5 km with speeds ranging from 0 to 30 km/h, 0 to 50 km/h and 0 to 100 km/h. Results include a quantitative and qualitative aspects, including the received signal strength indication (RSSI), signal-to-noise ratio (SNR), packet delivery ratio (PDR), and spreading factor (SF) for the received geographic coordinates. As the devices depend on the quality of the signal offered by the network, we also present the results of the development and evaluation of the LoRaWAN network, by planning its coverage throughout the city.

A comparative analysis of the platforms for decentralized autonomous organizations in the Ethereum blockchain

Blockchain technology has enabled a new kind of distributed systems. Beyond its early applications in Finance, it has also allowed the emergence of novel new ways of governance and coordination. The most relevant of these are the so-called Decentralized Autonomous Organizations (DAOs). DAOs typically implement decision-making systems to make it possible for their online community to reach agreements. As a result of these agreements, the DAO operates automatically by executing the appropriate portion of code on the blockchain network (e.g., hire people, delivers payments, invests in financial products, etc). In the last few years, several platforms such as Aragon, DAOstack and DAOhaus, have emerged to facilitate the creation of DAOs. As a result, hundreds of these new organizations have appeared, with their communities interacting mediated by blockchain. However, the literature has yet to appropriately explore empirically this phenomena. In this paper, we aim to shed light on the current state of the DAO ecosystem. We review the three main platforms nowadays (Aragon, DAOstack, DAOhaus) which facilitate the creation and management of DAOs. Thus, we introduce their main differences, and compare them using quantitative metrics. For such comparison, we retrieve data from both the main Ethereum network (mainnet) and a parallel Ethereum network (xDai). We analyze data from 72,320 users and 2,353 DAO communities in order to study the three ecosystems across four dimensions: growth, activity, voting system and funds. Our results show that there are notable differences among the DAO platforms in terms of growth and activity, and also in terms of voting results. Still, we consider that our work is only a first step and that further research is needed to better understand these communities, and evaluate their level of accomplishment in reaching decentralized governance.

Being a Mentor in open source projects

Mentoring is a well-known way to help newcomers to Open Source Software (OSS) projects overcome initial contribution barriers. Through mentoring, newcomers learn to acquire essential technical, social, and organizational skills. Despite the importance of OSS mentors, they are understudied in the literature. Understanding who OSS project mentors are, the challenges they face, and the strategies they use can help OSS projects better support mentors’ work. In this paper, we employ a two-stage study to comprehensively investigate mentors in OSS. First, we identify the characteristics of mentors in the Apache Software Foundation, a large OSS community, using an online survey. We found that less experienced volunteer contributors are less likely to take on the mentorship role. Second, through interviews with OSS mentors (n=18), we identify the challenges that mentors face and how they mitigate them. In total, we identified 25 general mentorship challenges and 7 sub-categories of challenges regarding task recommendation. We also identified 13 strategies to overcome the challenges related to task recommendation. Our results provide insights for OSS communities, formal mentorship programs, and tool builders who design automated support for task assignment and internship.

Using bundling to visualize multivariate urban mobility structure patterns in the São Paulo Metropolitan Area

Internet-based technologies such as IoT, GPS-based systems, and cellular networks enable the collection of geolocated mobility data of millions of people in large metropolitan areas. In addition, large, public datasets are made available on the Internet by open government programs, providing ways for citizens, NGOs, scientists, and public managers to perform a multitude of data analysis with the goal of better understanding the city dynamics to provide means for evidence-based public policymaking. However, it is challenging to visualize huge amounts of data from mobility datasets. Plotting raw trajectories on a map often causes data occlusion, impairing the visual analysis. Displaying the multiple attributes that these trajectories come with is an even larger challenge. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. In this paper, we augment a recent bundling technique to support multi-attribute trail datasets for the visual analysis of urban mobility. Our case study is based on the travel survey from the São Paulo Metropolitan Area, which is one of the most intense traffic areas in the world. The results show that bundling helps the identification and analysis of various mobility patterns for different data attributes, such as peak hours, social strata, and transportation modes.

Evaluating QualiCO: an ontology to facilitate qualitative methods sharing to support open science

Qualitative science methods have largely been omitted from discussions of open science. Platforms focused on qualitative science that support open science data and method sharing are rare. Sharing and exchanging coding schemas has great potential for supporting traceability in qualitative research as well as for facilitating the reuse of coding schemas. In this study, we present and evaluate QualiCO, an ontology to describe qualitative coding schemas. Twenty qualitative researchers used QualiCO to complete two coding tasks. In our findings, we present task performance and interview data that focus participants’ attention on the ontology. Participants used QualiCO to complete the coding tasks, decreasing time on task, while improving accuracy, signifying that QualiCO enabled the reuse of qualitative coding schemas. Our discussion elaborates some issues that participants had and highlights how conceptual and prior practice frames their interpretation of how QualiCO can be used.