scholarly journals Asia Network: An API-based cyberinfrastructure for the flexible topologies of digital humanities research in Sinology

2018 ◽  
Author(s):  
Hou Ieong Ho ◽  
Sean H. Wang ◽  
Pascal Belouin ◽  
Shih-Pei Chen
Keyword(s):  
Digital Humanities ◽  
Large Scale ◽  
Fair Use ◽  
Third Party ◽  
Infrastructure Development ◽  
Asian Studies ◽  
Loosely Coupled ◽  
Application Programming ◽  
Programming Interfaces ◽  
Research Tools

Digital humanities (DH) is a burgeoning field of research in Sinology and Asian studies more broadly, and its diversity and maturity necessitate a cyberinfrastructure fit for DH-focused Sinologists’ specific needs. “Asia Network” is our solution. It is a pioneering approach for resource dissemination and emerging data analytics (such as text mining and other fair-use, consumptive research techniques) in the humanities. It is a language-agnostic software that facilitates the secure linkage between third-party research tools to different third-party textual collections (both licensed and open-access ones) via application programming interfaces (APIs). It revolutionizes how scholars can work with textual sources by promoting a flexible, networked approach to e-infrastructure development. Crucially, Asia Network is a loosely-coupled software with flexible topologies; it can enable both federated or centralized linkages, and it can even “disappear” as long as its API standards remain in place to facilitate communications among databases and tools in the back-end. Thus, unlike large-scale infrastructural projects, Asia Network actively lowers the profile of centralized infrastructure and instead promotes existing tools and resources by enabling their interoperability. As a result, it allows scholars to fully leverage the potential of material digitization and digital research tools without re-creating silos of resources in the digital realm.

scholarly journals DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning

2017 ◽  
Author(s):  
Xiaodong Gu ◽  
Hongyu Zhang ◽  
Dongmei Zhang ◽  
Sunghun Kim
Keyword(s):  
Sequence Learning ◽  
Large Scale ◽  
Intelligent System ◽  
State Of The Art ◽  
Source Code ◽  
Computer Programs ◽  
Experimental Results ◽  
Multiple Devices ◽  
Application Programming ◽  
Programming Interfaces

Computer programs written in one language are often required to be ported to other languages to support multiple devices and environments. When programs use language specific APIs (Application Programming Interfaces), it is very challenging to migrate these APIs to the corresponding APIs written in other languages. Existing approaches mine API mappings from projects that have corresponding versions in two languages. They rely on the sparse availability of bilingual projects, thus producing a limited number of API mappings. In this paper, we propose an intelligent system called DeepAM for automatically mining API mappings from a large-scale code corpus without bilingual projects. The key component of DeepAM is based on the multi-modal sequence to sequence learning architecture that aims to learn joint semantic representations of bilingual API sequences from big source code data. Experimental results indicate that DeepAM significantly increases the accuracy of API mappings as well as the number of API mappings when compared with the state-of-the-art approaches.

Mashup Service Recommendation Based on Usage History and Service Network

2013 ◽  
Vol 10 (4) ◽  
pp. 82-101 ◽  
Author(s):  
Buqing Cao ◽  
Jianxun Liu ◽  
Mingdong Tang ◽  
Zibin Zheng ◽  
Guangrong Wang
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Web Applications ◽  
Rapid Development ◽  
Prototype System ◽  
Service Recommendation ◽  
Service Usage ◽  
Service Network ◽  
Application Programming ◽  
Programming Interfaces

With the rapid development of Web2.0 and its related technologies, Mashup services (i.e., Web applications created by combining two or more Web APIs) are becoming a hot research topic. The explosion of Mashup services, especially the functionally similar or equivalent services, however, make services discovery more difficult than ever. In this paper, we present an approach to recommend Mashup services to users based on usage history and service network. This approach firstly extracts users' interests from their Mashup service usage history and builds a service network based on social relationships information among Mashup services, Web application programming interfaces (APIs) and their tags. The approach then leverages the target user's interest and the service social relationship to perform Mashup service recommendation. Large-scale experiments based on a real-world Mashup service dataset show that the authors' proposed approach can effectively recommend Mashup services to users with excellent performance. Moreover, a Mashup service recommendation prototype system is developed.

Provisioning Converged Applications and Services via the Cloud

2013 ◽  
pp. 248-269
Author(s):  
Michael Adeyeye
Keyword(s):  
Large Scale ◽  
Hybrid Architecture ◽  
Web Browsers ◽  
Internet Applications ◽  
Rich Internet Applications ◽  
Content Sharing ◽  
Huge Data ◽  
Rich Media ◽  
Application Programming ◽  
Programming Interfaces

The cloud is becoming an atmosphere to store huge data and deploy massive applications. Using virtualization technologies, it is economical and feasible to provide testbeds in the cloud. The convergence of Next Generation (NG) networks and Internet-based applications may result in the deployment of future rich Internet applications and services in the cloud. This chapter shows the migration of mobility-enabled services to the cloud. It presents a SIP-based hybrid architecture for Web session mobility that offers content sharing and session handoff between Web browsers. The implemented system has recently evolved to a framework for developing different kinds of converged services over the Internet, which are similar to services offered by Google Wave and existing telephony Application Programming Interfaces (APIs). In addition, the work in this chapter is compared with those similar technologies. Lastly, the authors show efforts to migrate the SIP/HTTP application server to the cloud, which was necessitated by the need to include more functionalities (i.e., QoS and rich media support) as well as to provide large-scale deployment in a multi-domain scenario.

Quality of Service Management by Third Party in the Evolved Packet System

2012 ◽  
pp. 276-305
Author(s):  
Ivaylo Atanasov ◽  
Evelina Pencheva
Keyword(s):  
Quality Of Service ◽  
Service Management ◽  
Network Control ◽  
Third Party ◽  
Service Access ◽  
Qos Management ◽  
Protocol Conversion ◽  
Application Programming ◽  
Programming Interfaces

The chapter investigates the capabilities for open access to quality of service management in the Evolved Packet System. Based on the analysis of requirements for policy and charging control in the Evolved Packet Core, functions for quality of service (QoS) management and charging, available for third party applications, are identified. The functionality of Open Service Access (OSA) and Parlay X interfaces is evaluated for support of dynamic QoS control on user sessions. An approach to development of OSA-compliant application programming interfaces for QoS management in the Evolved Packet System is presented. The interface’s methods are mapped onto the messages of network control protocols. Aspects of interface implementation are discussed, including interface to protocol conversion.

Case Studies Using Adobe™ Flex

2014 ◽  
pp. 210-226
Keyword(s):  
Web Services ◽  
Case Studies ◽  
Third Party ◽  
Internet Applications ◽  
Rich Internet Applications ◽  
Representational State Transfer ◽  
State Transfer ◽  
Application Programming ◽  
Restful Web Services ◽  
Programming Interfaces

REpresentational State Transfer (REST) is an architectural style that has recently emerged as a new approach to develop and deliver Web services. In fact, a great number of companies, such as eBay™, Twitter™, and Amazon.com™, have adopted REST to deliver Web services and Web feeds. This chapter offers a review of the support for consuming RESTful Web services in Adobe™ Flex™; then, it presents two case studies about the development of third-party RESTful Web services-based Rich Internet Applications (RIAs) using Adobe Flex™ along with HyperText Markup Languages (HTML) and JavaScript. The case studies presented in this chapter are intended to explain the common prerequisites for using RESTful Web services Application Programming Interfaces (APIs) as well as the particular implementation details, including the challenges and alternatives facing the capabilities and limitations of the target technologies. In addition, they exemplify the use of some User Interface (UI) patterns.

scholarly journals Automation, APIs and the distributed labour of platform pedagogies in Google Classroom

2020 ◽  
Author(s):  
Carlo Perrotta
Keyword(s):  
Third Party ◽  
Digital Data ◽  
Data Interoperability ◽  
Digital Platforms ◽  
Original Analysis ◽  
Application Programming ◽  
Cross Platform ◽  
Working Practices ◽  
Pedagogic Practices ◽  
Programming Interfaces

Digital platforms have become central to interaction and participation in contemporary societies. New forms of ‘platformized education’ are rapidly proliferating across education systems, bringing logics of datafication, automation, surveillance, and interoperability into digitally mediated pedagogies. This article presents a conceptual framework and an original analysis of Google Classroom as an infrastructure for pedagogy. Its aim is to establish how Google configures new forms of pedagogic participation according to platform logics, concentrating on the cross-platform interoperability made possible by application programming interfaces (APIs). The analysis focuses on three components of the Google Classroom infrastructure and its configuration of pedagogic dynamics: Google as platform proprietor, setting the ‘rules’ of participation; the API which permits third-party integrations and data interoperability, thereby introducing automation and surveillance into pedagogic practices; and the emergence of new ‘divisions of labour’, as the working practices of school system administrators, teachers and guardians are shaped by the integrated infrastructure, while automated AI processes undertake the ‘reverse pedagogy’ of learning insights from the extraction of digital data. The article concludes with critical legal and practical ramifications of platform operators such as Google participating in education.

scholarly journals THE EVOLUTION OF FACEBOOK'S GRAPH API

2020 ◽  
Author(s):  
Marcus Burkhardt ◽  
Anne Helmond ◽  
Tatjana Seitz ◽  
Fernando Van der Vlist
Keyword(s):  
Data Structures ◽  
Historical Analysis ◽  
Data Retrieval ◽  
Third Party ◽  
Internet Archive ◽  
Privacy Concerns ◽  
Empirical Perspective ◽  
Application Programming ◽  
Data Objects ◽  
Programming Interfaces

Facebook’s application programming interfaces (APIs) enable third-party app developers to access data and functionality and have become central to many of the platform’s ongoing data scandals and privacy concerns. Understanding how the platform and its APIs evolve and how it responds to issues requires looking closely and empirically at the evolution of access points, data structures, and graph data structures. The technicity of APIs is crucial for understanding the politics of data sharing and how APIs represent and structure phenomena and temporarily stabilise them. Instead of using APIs as an umbrella term for data retrieval, we conduct historical “technical fieldwork” for examining the evolving architecture and interfaces of Facebook’s web APIs. We contribute an in-depth technical and empirical perspective on the evolution of Facebook’s Graph API since 2006, and how it evolved into one of the most significant web APIs and an integral part of contemporary advertising infrastructures and web development cultures. Our empirical historical analysis of Facebook’s Graph API is based on the entire corpus of available archived developer documentation held by the Internet Archive. As we show, key changes in the Graph API evolution are characterized by phases of experimentation, standardization, commercialization, and regulation. We provide a “scalable reading” of the evolution of Facebook’s Graph API which provides insights in how data and data flows are governed through changes in data structures and permissions. By considering the evolving structures of APIs and individual data objects, we may develop further empirically informed critiques of platforms, APIs, and their data.

scholarly journals Multiparty Call Control at the Network Edge

2020 ◽  
Vol 26 (5) ◽  
pp. 39-49
Author(s):  
Ivaylo I. Atanasov ◽  
Evelina N. Pencheva ◽  
Denitsa L. Velkova ◽  
Ivaylo P. Asenov
Keyword(s):  
Data Model ◽  
Third Party ◽  
Call Control ◽  
Fifth Generation ◽  
Application Programming ◽  
State Models ◽  
Session State ◽  
Multi Access ◽  
Programming Interfaces ◽  
Network Programmability

Network programmability is a key feature of fifth generation (5G) system which, in combination with cloud-based services, can support many use cases, including mission critical and healthcare communications. Programmability enables flexibility in customization of service connectivity. Multi-access Edge Computing (MEC) services and applications are enablers for network programmability. In this paper, MEC capabilities for programmability of multiparty multimedia call control at the network edge are studied. Multiparty video calls are one of the key applications of 5G, and are efficient way to exchange ideas, knowledge, expertise, information, and so on. The paper presents an approach to design MEC Application Programming Interfaces (APIs) which enable third party applications to create multiparty multimedia sessions and dynamically manage session participations. The API functionality is described by required information and message flows. The paper specifies the proposed MEC API with data model. Feasibility study includes modelling and formal validation of multiparty session state models supported by the network and mobile edge application. The latency injected by the API is evaluated by emulation.

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