Efficient data representation for XML in peer-based systems

Purpose - New directions in the provision of end-user computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for data-intensive applications on such platforms. The partitioned structure can be compressed using dictionary-based approaches and then directly queried without firstly decompressing the whole structure. Design/methodology/approach - The paper describes an architecture for partitioning XML into structural and dictionary elements and the subsequent manipulation of the dictionary elements to make the best use of available space. Findings - The results indicate that considerable savings are available by removing duplicate dictionaries. The paper also identifies the most effective strategy for defining dictionary scope. Research limitations/implications - This evaluation is based on a range of benchmark XML structures and the approach to minimising dictionary size shows benefit in the majority of these. Where structures are small and regular, the benefits of efficient dictionary representation are lost. The authors' future research now focuses on heuristics for further partitioning of structural elements. Practical implications - Mobile applications that need access to large data collections will benefit from the findings of this research. Traditional client/server architectures are not suited to dealing with high volume demands from a multitude of small mobile devices. Peer data sharing provides a more scalable solution and the experiments that the paper describes demonstrate the most effective way of sharing data in this context. Social implications - Many services are available via smartphone devices but users are wary of exploiting the full potential because of the need to conserve battery power. The approach mitigates this challenge and consequently expands the potential for users to benefit from mobile information systems. This will have impact in areas such as advertising, entertainment and education but will depend on the acceptability of file sharing being extended from the desktop to the mobile environment. Originality/value - The original work characterises the most effective way of sharing large data sets between small mobile devices. This will save battery power on devices such as smartphones, thus providing benefits to users of such devices

An extension of SPARQL for expressing qualitative preferences

In this paper we present SPREFQL, an extension of the SPARQL language that allows appending a PREFER clause that expresses "soft" preferences over the query results obtained by the main body of the query. The extension does not add expressivity and any SPREFQL query can be transformed to an equivalent standard SPARQL query. However, clearly separating preferences from the "hard" patterns and filters in the WHERE clause gives queries where the intention of the client is more cleanly expressed, an advantage for both human readability and machine optimization. In the paper we formally define the syntax and the semantics of the extension and we also provide empirical evidence that optimizations specific to SPREFQL improve run-time efficiency by comparison to the usually applied optimizations on the equivalent standard SPARQL query.Comment: Accepted to the 2017 International Semantic Web Conference, Vienna, October 201

THE OPERATIONAL ASPECTS OF OPEN AND DISTANCE LEARNING AND ITS QUALITY ASSURANCE SYSTEM IN UNIVERSITAS TERBUKA

Universitas Terbuka (UT) telah berfungsi sejak 1984 untuk memperluas kesempatan belajar bagi seluruh warga negara Indonesia dari berbagai lapisan guna menempuh pendidikan tinggi berkualitas. Makalah ini menyajikan aspek operasional pendidikan terbuka dan jarak jauh beserta sistem penjaminan kualitas UT. Deskripsi dan analisis tentang UT disampaikan dalam hal sistem pembelajaran, asesmen pembelajaran, dan sistem pendukung layanan operasional. Beragam layanan pendukung pembelajaran diberikan sesuai kebutuhan mahasiswa meliputi pembelajaran jarak jauh dengan tutorial online, pembelajaran jarak jauh blended dengan tutorial tatap muka dan online, pembelajaran jarak jauh dengan semua matakuliah didukung tutorial tatap muka, dan pembelajaran fully online. Sistem penjaminan kualitas UT meliputi pengembangan budaya kerja berkualitas sebagai tanggung jawab bersama, fokus pada pencegahan, dan pengembangan mekanisme asesmen kualitas secara internal dan eksternal. UT telah mengadopsi Asian Association of Open Universities (AAOU) Quality Assurance Framework sejak tahun 2001. Asesmen dan review kualitas secara eksternal telah dilakukan melalui sertifikasi ISO 9001 dan ISO 27001, akreditasi Program Studi dan Institusi oleh Badan Akreditasi Nasional Perguruan Tinggi (BAN-PT), dan review kualitas oleh International Council for Open and Distance Education (ICDE). Arah ke depan UT sebagaimana dinyatakan oleh Menteri Riset, Teknologi, dan Pendidikan Tinggi 2014-2015 adalah tantangan UT sebagai pelopor cyber university di Indonesia serta menyediakan matakuliah online bagi mahasiswa dari perguruan tinggi di Indonesia lain agar memiliki pengalaman pembelajaran online. Universitas Terbuka (UT) has been functioning since 1984 to widen opportunities for the citizens of Indonesia from all geographical, social and economic backgrounds to have access to quality higher education. This paper presents the UT operational aspects of open and distance learning and its quality assurance system. The description and analysis of UT is presented in terms of teaching and learning system, assessment of student learning, and operational support system. The UT modes of learning support to students are provided based on the students’ needs to include distance learning with online tutorials, blended distance learning with face-to-face and online tutorials, distance learning with all courses supported by face-to-face tutorials, and fully online learning courses. Quality assurance is discussed in terms of the development of quality work culture as shared responsibility, focus on prevention, and the establishment of mechanism for internal and external assessment. UT has adopted the Asian Association of Open Universities (AAOU) Quality Assurance Framework since 2001. External quality assessment includes certification for ISO 9001 and ISO 27001, Study Program and Institution accreditations by the National Board of Higher Education Accreditation (BAN-PT), and quality reviews by the International Council for Open and Distance Education (ICDE). Future directions of UT as stated by the former Minister of Research, Technology, and Higher Education was to be pioneer in cyber university and to provide online courses for students from other universities in Indonesia

Towards Mobility Data Science (Vision Paper)

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state of the art and describe open challenges for the research community in the coming years.Comment: Updated arXiv metadata to include two authors that were missing from the metadata. PDF has not been change

Mining Closed Itemsets for Coherent Rules: An Inference Analysis Approach

Past observations have shown that a frequent item set mining algorithm are alleged to mine the closed ones because the finish offers a compact and a whole progress set and higher potency. Anyhow, the most recent closed item set mining algorithms works with candidate maintenance combined with check paradigm that is dear in runtime likewise as area usage when support threshold is a smaller amount or the item sets gets long. Here, we show, PEPP with inference analysis that could be a capable approach used for mining closed sequences for coherent rules while not candidate. It implements a unique sequence closure checking format with inference analysis that based mostly on Sequence Graph protruding by an approach labeled Parallel Edge projection and pruning in brief will refer as PEPP. We describe a novel inference analysis approach to prune patterns that tends to derive coherent rules. A whole observation having sparse and dense real-life information sets proved that PEPP with inference analysis performs larger compared to older algorithms because it takes low memory and is quicker than any algorithms those cited in literature frequently