Search Results (31)

Sustainable tourism minimises the adverse impact of tourism on the natural environment and local culture while stimulating the socioeconomic development of regions or even countries. Geoportals and (geo)informational mashup portals significantly affect sustainable tourism planning through modern computer solutions for more sustainable planning of tourist activities on the demand and supply sides. This study had two research aims: (1) to develop a checklist for assessing the functionality of tourist geoportals and evaluate it and (2) to assess the inventory of functions useful for sustainable tourism planning available at selected geoportals with the checklist. The aims were pursued with an original research tool, the Functionality Assessment Checklist (FAC). The FAC is a set of original criteria useful for assessing the quality of tourist geoportals. This study investigated the following research questions: (Q1) What functions should be included on a checklist for assessing the functionality of geoportals useful for sustainable tourism planning? (Q2) What functions should be included in a geoportal to facilitate sustainable tourism planning? The original contributions of this article are (1) the checklist for assessing the functionality of tourist geoportals and (2) the assessment of the impact of geoportal’s functionality on the possibility of planning sustainable tourism. The functionality assessment revealed that the tested geoportals have most of the tourism, informational, educational, and use-related functions. This suggests they can be useful for sustainable tourism planning. Full article

Organized as part of the annual Art Days festival in the capital of the Latvian SSR, the First Exhibition of Approximate Art comprised a cacophonous and provocative mashup of music, dance, performance art, and design. At the center of the event was a demonstration of mixing and scratching records by Maximilian Lenz, also known as Westbam, one of the leading DJs in West Berlin. Mining archival sources in Berlin and Riga, this article reconstructs the complicated path by which the DJ came to perform at the event. It reveals a surprising network of relations and alliances operating in tandem behind the scenes, featuring a Riga artist dedicated to enacting a vision of postmodern performance in his city, an ambitiously networking émigré Latvian living in exile in West Germany, and a pair of Soviet offices under direct control of the KGB, charged with managing cultural exchanges with the West in hopes of currying sympathies for Soviet culture and policy. Complementing and extending research on the “gaps” and “holes” in the Soviet system that sometimes allowed for the staging of otherwise unacceptable works of art, the story of the First Exhibition of Approximate Art reveals how personal connections and interpersonal networks within even the most highly monitored parts of the system itself—the state security apparatus—could open doors for artistic projects unanticipated and even undesired by the bureaucratic state. Full article

Mashups, which combine various web application programming interfaces (APIs) to implement some complex requirements, have grown to be a popular technique for developing service-oriented software. However, recommending suitable cloud APIs for mashup creation is challenging due to the rapidly increasing number of comparable APIs. Many existing mashup-oriented cloud API recommendations focus on functional similarity and ignore functional complementarity, which significantly impacts the accuracy of the recommendation results. Therefore, this paper proposed a feature representation and recommendation method for cloud APIs that fuses both similarity and complementarity. A heterogeneous information network of the cloud API ecosystem was constructed, and the neighbors, based on metapaths, were aggregated using a self-attention mechanism to generate the features of similarity and complementarity for the cloud APIs. Then, the mashup-related attention was utilized to fuse the two features, taking into consideration the varying preferences of different mashups towards similarity and complementarity features of cloud APIs. This fusion resulted in features that align cloud APIs with mashup requirements, which were employed to predict the probability of the mashup invoking a particular candidate cloud API. The proposed method was evaluated on a real dataset, and the results showed that it outperforms the baseline method and enhances the performance of mashup-oriented cloud API recommendations. Full article

Web API is an efficient way for Service-based Software (SBS) development, and mashup is a key technology which merges several web services to deal with the increasing complexity of software requirements and expedite the service-based system development. The efficient service recommendation method is vital for the software development. However, the existing methods often suffer from data sparsity or cold start issues, which should lead to bad effects. Currently, this paper starts with SBS development, and proposes a service recommendation method based on knowledge graph embedding and collaborative filtering (CF) technology. In our model, we first construct a refined knowledge graph using SBS-service co-invocation record and SBS and service related information to mine the potential semantics relationship between SBS and service. Then, we learn the SBS and service entities in the knowledge graph. These heterogeneous entities (SBS and service, etc.) are embedded into the low-dimensional space through the representation learning algorithms of Word2vec and TransR, and the distances between SBS and service vectors are calculated. The input of recommendation model is SBS requirement (target SBS), the similarities functional SBS set is extracted from knowledge graph, which can relieve the cold start problem. Meanwhile, the recommendation model uses CF to recommend service to target SBS. Finally, this paper verifies the effectiveness of method on the real-word dataset. Compared with the several state-of-the-art methods, our method has the best service hit rate and ranking quality. Full article

Service-oriented computing has become a popular area of research, with a particular focus on service composition. There have been many developments in this field, such as new techniques for data engineering in service description languages, protocols for publication and discovery, the optimization of service selection and scheduling, and the deployment and monitoring of composed services. However, this diversity of approaches and methodologies can make it challenging to navigate between different proposed solutions and identify research gaps. In order to provide a clearer understanding of this body of work, this paper presents a comprehensive framework for the taxonomy of service composition approaches, methodologies, and tools. This framework proposes a structured view of different perspectives, such as formal, semantic, and automatic approaches, with a particular focus on the end-user’s perspective and tools such as Mashups. Full article

The term “Western Message Petroglyphs” (WMPs) refers to a number of petroglyph sites found scattered among eight western states that are recognized by their shared image content and layout. The imagery is drawn largely from a mash-up of late historic Native American sign-gesture language and picture-writing traditions inter-mixed with pan-cultural imagery from around the world. An increasing number of sites that fit this mold have been reported over the past 85 years or so, currently numbering 39 in all. There is no question that these sites date to post-European contact based on images in some panels that depict Euro-American cultural content (e.g., western-style house, rifle, whiskey keg, horse, etc.). The post-contact era is also apparent in the method used in rendering the engraved images evidenced by the smooth angular lines and chisel strikes produced by metal tools. This paper focuses on narrowing the time frame for these sites based on two additional streams of evidence. First, patterned associations with historic landscape settings tied to the era of western expansion bind the sites together into a coherent whole and set a floor for their oldest probable dates. An example of four sites located in Utah and Arizona illustrates their connection to the last quarter of the nineteenth century and the opening years of the twentieth. Secondly, a study of their imagery supports the proposed dates by revealing a “smoking gun” for the source of many of the individual icons. An example of the methodology used to translate a Western Message Petroglyph panel is described, and a profile of the central author who appears to have acted with a small group of others is suggested in order to aid in the search for this person(s) in the historic record of the American West. Full article

Mashup is a new type of application that integrates multiple Web APIs. For mashup application development, the quality of the selected APIs is particularly important. However, with the rapid development of Internet technology, the number of Web APIs is increasing rapidly. It is unrealistic for mashup developers to manually select appropriate APIs from a large number of services. For existing methods, there is a problem of data sparsity, because one mashup is related to a few APIs, and another problem of over-reliance on semantic information. To solve these problems in current service discovery approaches, we propose a service discovery approach based on a knowledge map (SDKG). We embed service-related information into the knowledge graph, alleviating the impact of data sparsity and mining deep relationships between services, which improves the accuracy of service discovery. Experimental results show that our approach has obvious advantages in accuracy compared with the existing mainstream service discovery approaches. Full article

With the rapid development of service-oriented computing, an overwhelming number of web services have been published online. Developers can create mashups that combine one or multiple services to meet complex business requirements. To speed up the mashup development process, recommending suitable services for developers is a vital problem. In this paper, we address the data sparsity and cold-start problems faced in service recommendation, and propose a novel multi-relational graph convolutional network framework (MRGCN) for service recommendation. Specifically, we first construct a multi-relational mashup-service graph with three types of relations, namely composition relation, functional relation, and tagging relation. These three relations are indispensable and complement each other for capturing multi-view information. Then, the three relations in the graph are seamlessly fused with various strategies. Next, graph convolution is performed on the fused multi-relational graph to capture the high-order relational information between mashups and services. Finally, the relevance between mashup requirements and services is predicted based on the learned features on the graph. We conduct extensive experiments on the ProgrammableWeb dataset and demonstrate that our proposed method can outperform state-of-the-art methods in recommending services when only mashup requirements are available. Full article

The sixth generation (6G) of communication networks represents more of a revolution than an evolution of the previous generations, providing new directions and innovative approaches to face the network challenges of the future. A crucial aspect is to make the best use of available resources for the support of an entirely new generation of services. From this viewpoint, the Web of Things (WoT), which enables Things to become Web Things to chain, use and re-use in IoT mashups, allows interoperability among IoT platforms. At the same time, Multi-access Edge Computing (MEC) brings computing and data storage to the edge of the network, which creates the so-called distributed and collective edge intelligence. Such intelligence is created in order to deal with the huge amount of data to be collected, analyzed and processed, from real word contexts, such as smart cities, which are evolving into dynamic and networked systems of people and things. To better exploit this architecture, it is crucial to break monolithic applications into modular microservices, which can be executed independently. Here, we propose an approach based on complex network theory and two weighted and interdependent multiplex networks to address the Microservices-compliant Load Balancing (McLB) problem in MEC infrastructure. Our findings show that the multiplex network representation represents an extra dimension of analysis, allowing to capture the complexity in WoT mashup organization and its impact on the organizational aspect of MEC servers. The impact of this extracted knowledge on the cognitive organization of MEC is quantified, through the use of heuristics that are engineered to guarantee load balancing and, consequently, QoS. Full article

In recent years, information integration systems have become very popular in mashup-type applications. Information sources are normally presented in an individual and unrelated fashion, and the development of new technologies to reduce the negative effects of information dispersion is needed. A major challenge is the integration and implementation of processing pipelines using different technologies promoting the emergence of advanced architectures capable of processing such a number of diverse sources. This paper describes a semantic domain-adaptable platform to integrate those sources and provide high-level functionalities, such as recommendations, shallow and deep natural language processing, text enrichment, and ontology standardization. Our proposed intelligent domain-adaptable platform (IDAP) has been implemented and tested in the tourism and biomedicine domains to demonstrate the adaptability, flexibility, modularity, and utility of the platform. Questionnaires, performance metrics, and A/B control groups’ evaluations have shown improvements when using IDAP in learning environments. Full article

Virtual learning environments contain valuable data about students that can be correlated and analyzed to optimize learning. Modern learning environments based on data mashups that collect and integrate data from multiple sources are relevant for learning analytics systems because they provide insights into students’ learning. However, data sets involved in mashups may contain personal information of sensitive nature that raises legitimate privacy concerns. Average privacy preservation methods are based on preemptive approaches that limit the published data in a mashup based on access control and authentication schemes. Such limitations may reduce the analytical utility of the data exposed to gain students’ learning insights. In order to reconcile utility and privacy preservation of published data, this research proposes a new data mashup protocol capable of merging and k-anonymizing data sets in cloud-based learning environments without jeopardizing the analytical utility of the information. The implementation of the protocol is based on linked data so that data sets involved in the mashups are semantically described, thereby enabling their combination with relevant educational data sources. The k-anonymized data sets returned by the protocol still retain essential information for supporting general data exploration and statistical analysis tasks. The analytical and empirical evaluation shows that the proposed protocol prevents individuals’ sensitive information from re-identifying. Full article

Innovation is a crucial force underlying the organizational and societal ability to survive and thrive in crisis times, especially in education. However, not all challenges require creating novel solutions; occasionally, combining pre-existing solutions—an approach known as the mashup methodology—can provide equal benefit. Nevertheless, this approach appears to be relatively unknown. In the current case study, we provide an example of using a mashup of technologies to solve the challenge of running a remote virtual hackathon under COVID-19 social distancing regulations. Additionally, we argue that utilizing the mashup is a form of modeling, in which students learn by witnessing its use. Utilizing the Technology Acceptance Model, we show that by modeling the use of the mashup methodology in this hackathon (Study 1—case), we managed to improve students’ attitudes towards the method and increase its perceived usefulness and ease of use in their eyes. This, in turn, raised their intention to use it as an innovation tool in the future. Study 2 revealed that this effect on participants’ intentions is more significant than what would be achieved by merely teaching people about the methodology. The results of these studies add to the growing literature emphasizing the importance of using digital innovations as means of improving the quality of education, thus increasing the satisfaction and well-being of students. Full article

Service Mashups can help users to integrate data of multiple sources based on Web services composition. Considering a kind of sustainable service Mashup whose data requirement cannot be predetermined, so users need to choose and compose services in a tentative manner. Meanwhile, users can choose and compose services continually to obtain more data based on existing composition results. In such Mashups, a Web service is chosen according to the data provided by the service. Because it is difficult for users to choose from large amounts of services manually, it is a challenge to recommend services instantly for users during the construction of a sustainable service Mashup. This paper proposes an approach to recommend Web services instantly for a sustainable service Mashup. According to the services used in the service Mashup under construction, candidate services are chosen based on the Mashups that are similar to the constructing Mashup, as well as the parameter correlations of services from the perspective of actual operations of Web service composition. Experimental results indicate that the proposed approach has better precision, recall, and coverage values compared to existing state-of-the-art approaches, and therefore, it is more suitable for instant service recommendation of sustainable service Mashups. Full article

The Beverage Guidance System has established dietary recommendations for daily intake of commonly consumed beverages including water, tea, coffee, milk, non-calorically sweetened beverages, and calorically sweetened beverages. As obesity in America continues to be a growing problem, this guidance becomes of increasing importance due to many beverages’ potential links to Type 2 Diabetes Mellitus (T2DM), Cardiovascular disease (CVD), and numerous other harmful health effects. However, the growing popularity of “better for you” beverages is causing a shift in the market, with consumers pushing for healthier beverage alternatives. Beverages simultaneously present advantages while posing concerns that need to be evaluated and considered. In this review, health effects of nonalcoholic beverages are discussed including various aspects of consumption and current trends of the beverage market such as the novel Soft Seltzer category as an alternative to Hard Seltzer and various mashups. A variety of advisory boards and agencies responsible for dietary guidelines in various countries suggest drinking water as the preferred practice for hydration. Full article

Ordinary web users can now create and publish online content. They even venture into “mashups,” integrating information from different sources into a composite information-providing web service. This is a non-trivial design task, which falls into the area of end-user development when the ordinary users who perform it do not have programming education. In this article, we investigate the service design strategies of 12 such ordinary users and compare them against the baseline of 12 programmers. In our think-aloud study, users completed two contrasting types of tasks involved in developing service-based applications: (a) manual service composition and (b) parametric design using templates with a high degree of software support (or assisted composition). These service composition tasks were chosen to differ in respect to the level of user support provided by the tool. Our findings show that non-programmers liked, more than programmers, the template-based parametric design and did not find the tool assistance as constraining as the programmers did. The difficulty of design involved in manual service composition and the absence of user guidance hindered non-programmers in expressing and implementing accurate design solutions. The differences in the mental models and needs of non-programmers are established to be in stark contrast to those of programmers. We used the details of our findings to propose specialized design recommendations for service composition tools aligned with the profiles of their target users. Full article