Browsing and visualizing digital bibliographic data

Big data is becoming bigger every day. Even for simple applications such as the Digital Bibliography & Library Project (DBLP) database, the data is becoming unmanageable using the conventional databases because of its size. Applying big data processing methods such as Hadoop and Spark is becoming more popular because of that. In this work, we investigate the use of Hadoop and Spark in the querying process of big data and we compare the performance of them in terms of their execution time. We use the DBLP database as a case study. Results show that Hadoop and Spark enhances the query execution time significantly when compared with conventional database management systems. We also found that Spark enhances the execution time over Hadoop.

The problem with Author Name Disambiguation is to determine whether the same name in the bibliographic archive refers to the same author or not. Currently, author identification on The Labeled Digital Bibliography and Library Project (DBLP) is triggered by a request for an author who finds his publication mixed with other people's writing. Name ambiguity leads to incorrect identification and attribution of credit to authors. Despite much research in the last decade, the issue of ambiguity of the author's name remains largely unsolved. In this paper, the Capsule Networks (CapsNets) method is proposed to resolve the ambiguity of the author's name. The proposed method obtains the best accuracy in four Name Disambiguation problems including homonyms, synonyms, and non-homonyms synonyms, which is an average of 99% on training and testing data. Likewise, the overall data tested has an accuracy of 99.83% with a low error value. In addition, CapsNets were tested with Performance Measurements including Sensitivity, Precision, and F1-Score. Capsnets can identify authors in DBLP bibliographic data by using a number of attributes such as author name, co-author, venue, title, and year.

Many heuristic algorithms have been proposed in the literature to solve the team formation problem. The researchers considered a project as a set of skills selected randomly from the given pool of skills. But this leads to a skewed distribution of skills in the projects with many skills having very few experts, which we term as rare skills. In this work, we create a realistic bench-mark dataset for this problem. In general, any project/task in the industry can be seen to have a good mix of popular as well as rare skills. We first conduct an empirical study of the distribution of popular skills vs rare skills in the well-known DBLP (Digital Bibliography & Library Project) data set. The distribution of popularity of skills is shown to satisfy a power law with a heavy tail, indicating the presence of a large number of skills with very few experts and a small number of highly popular skills. We build a realistic a benchmark dataset using stratified random sampling to form tasks with various distributions of popular and rare skills. The classical team formation algorithms are evaluated using this new benchmark dataset. The evaluation is done with respect to the available communication costs in the literature as well as the execution time incurred by the algorithms. It has been observed from the experiments that all the measures show lower values of communication cost for tasks having higher proportion of popular skills.

The overwhelming usage of social and collaboration networks provides the opportunity to analyze evolution of relationships among individuals, like celebrities or co-authors. Discovering such phenomenon in large complex networks is non-trivial due to their large sizes. In this situation, the aggregation functions used in OLAP, are useful to analyze the summarized data. OLAP has successfully proven its worth on multidimensional or complex networks. However, existing aggregations in the current OLAP systems do not produce versatile results in case of social and collaboration networks. This happens because said type of networks have structural connectivity/links among nodes, which cannot be considered by OLAP during its execution. In this situation, a useful discovery in terms of identifying pairs of nodes whose relationships is emerging in recent time, is missed. Such discovery of pairs of nodes is important for various applications such as targeted marketing, future joint partnerships and predicting future correspondence to name a few. In this study, we call such pairs as Rising_Pairs and propose an aggregation function for performing OLAP on network data whose historical information is maintained over a period of times. Using structural information, Rising_Pairs, our proposed aggregation function, discovers the strongly coupled pairs in a network data by emphasizing their recent interactions and attribute similarities. In this way, useful information related to strongly coupled pairs in a network is identified. To verify the effectiveness of our proposal, we implemented it on various types of real-world networks like Facebook, Digital Bibliography and Library Project (DBLP) and Global Positioning System (GPS) trajectory datasets and observed interesting patterns.

Tools, techniques and protocols necessary for building up digital libraries have now fully evolved with computing power that allows parallel processing, multitasking, parallel consultation and parallel knowledge navigation and sohare tools that facilitate artificial intelligence and interadivity. Coincided with availability of sofhvare, hardware and networking technology, the advent of world wide web 0its, ever incr easing usage and highly evolved browsers have paved the way for creation of digital libraries. With rapid developments in technologies necessary for developing digital libraries, the world of digital information resources has expanded rapidly and exponentially. Increasing number of publishers are using the internet as a global way to offer their publications to the international community of scientists and technologists. With the technology available at an effordable cost, the libraries are initiating small digitisation projects as an individual library or as a group of libraries. Building-up digital collection and the infrastructure required to access them is a challenge that every library has to deal with. The article delves into technological evolution, cultural revolution and contents enrichment that led to revolution in growth and development of digital libraries. The artide has two distinct parts, while the first part deals with various aspects of building, accessing and organising digital resources and collection, the second part elaborates on the process, technology, formats, compression techniques and tools used in digital imaging. The article describes optical character recognition (OCR) and advocates for hybrid solution for preservation of digital information. http://dx.doi.org/10.14429/dbit.21.6.3547

The principles and methods of TQM (total quality management) were applied to digital library management. TQM puts emphasis on process control and continual improvement. The TQM theories and measures explained clearly in this paper were the scientific tools used in the experiment in the Wenzhou University Digital Library. This paper deals with a very broad range of subjects related to a digital library: system model of TQM for digital library, organization structure, and tasks of Wenzhou University Digital Library, task flow chart of electronic reading room, cause and effect of electronic reading room quality man- agement, systematic model of enhancing electronic information acquisition rate, quality comparison of electronic reading room service, etc.

We present here our findings of a study, part of larger research focusing on understanding the structure and composition of the academic community of Digital Library (DL). Using social network analysis, the present study analyses the structural features of editorial boards (EBs) of leading journals of DL. Following the premise that boundaries and directions of a field, especially an evolving one such as digital libraries is shaped by journals and their editors, we undertook a study of the editorial boards of the top 56 journals in the field of digital libraries. Techniques from social network analysis are applied to the data to reveal the structures and relationships within the EBs and journals of the DL community. The paper reveals the structure of the scientific grouping as well as the key players in the system and finds the ‘diversified convergence’ of fields. The focus is on the stars of the DL community as well as journals. We have compared the results with our previous studies carried out on different communication platforms of the DL world. Our results show that while computer science is the common thread, library and information science is the field that dominates, both in the scheme of things of top-ranking journals as well as editors.

We demonstrate GraphDBLP, a tool to allow researchers for querying the DBLP bibliography as a graph. The DBLP source data were enriched with semantic similarity relationships computed using wordembeddings. A user can interact with the system either via a Web-based GUI or using a shell-interface, both provided with three parametric and pre-defined queries. GraphDBLP would represent a first graph-database instance of the computer scientist network, that can be improved through new relationships and properties on nodes at any time, and this is the main purpose of the tool, that is freely available on Github. To date, GraphDBLP contains 5+ million nodes and 24+ million relationship.

The field of Scientometrics is concerned with the analysis of science and scientific research. As science advances, scientists around the world continue to produce large numbers of research articles, which provide the technological basis for worldwide collection, sharing, and dissemination of scientific discoveries. Research ideas are generally developed based on high quality citations. Understanding how research ideas emerge, evolve, or disappear as a topic, what is a good measure of quality of published works, what are the most promising areas of research, how authors connect and influence each other, who are the experts in a field, what works are similar, and who funds a particular research topic are some of the major foci of the rapidly emerging field of Scientometrics. Digital libraries and other databases that store research articles have become a medium for answering such questions. Citation analysis is used to mine large publication graphs in order to extract patterns in the data (e.g., citations per article) that can help measure the quality of a journal. Scientometrics, on the other hand, is used to mine graphs that link together multiple types of entities: authors, publications, conference venues, journals, institutions, etc., in order to assess the quality of science and answer complex questions such as those listed above. Tools such as maps of science that are built from digital libraries, allow different categories of users to satisfy various needs, e.g., help researchers to easily access research results, identify relevant funding opportunities, and find collaborators. Moreover, the recent developments in data mining, machine learning, natural language processing, and information retrieval makes it possible to transform the way we analyze research publications, funded proposals, patents, etc., on a web-wide scale. The workshop aims at bringing together researchers with diverse interdisciplinary backgrounds interested in mining large digital libraries and other relevant databases. The topics of interest include, but are not limited to:

Digital Libraries (DLs) are an access to the collections of electronic documents over network. They serve the scientific community with large amount of electronic data and thereby increase the levels of education and literacy in the society. Software agents have been proved to be the best for the handling of distributed information. This paper surveys about the digital libraries and software agents and analyses the adoption of agents for various issues of distributed DLs. http://dx.doi.org/10.14429/dbit.24.3.3625

The digital library is an information providing service in which all the information resources are available in computer process-able form. The functions of acquisition, storage, preservation, retrieval, access and display are carried out through the use of digital technologies. In this way we can say that Digital Libraries are the systems which provide users with coherent access to a very large, organized repository of information and knowledge. Digital Libraries may be accessed remotely by the users. The retrieval of information from a digital library database is easy and time saving process. Present paper discusses about features of a digital library, role of a digital library in dissemination of information, architecture of digital library, federal search model and its features, digital library standards, steps in building digital library and problems of digital initiatives in India in detail.

A partir da análise dos estudos realizados sobre o Portal de Periódicos da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), este trabalho propõe a criação de um indicador automático de avaliação da adequação do conteúdo do Portal à produção de teses e dissertações cadastradas na Biblioteca Digital Brasileira de Teses e Dissertações (BDTD) do Instituto Brasileiro de Informação em Ciência e Tecnologia (IBICT). São descritos os passos básicos para a criação desse indicador e as ponderações sobre a sua viabilidade tecnológica. Ao final, são discutidos possíveis impactos e a importância desse indicador para a avaliação da adequação do Portal de Periódicos da Capes em relação às necessidades informacionais da comunidade científica brasileira. O indicador forneceria informações para a implementação de medidas de adaptabilidade contínua do Portal às necessidades de seus usuários.

With the new method of information delivery for the library, the quality of service and Digital Library issues become paramount importance. Various model and framework have been proposed to evaluate the Quality of Service in Digital Library. Unfortunately, features that contribute towards the Digital Library services quality have not been factored into the design of most existing quality of services model in Digital Library. This paper presented a result of hypothesis testing which eventually proposed a new conceptual model on the service quality of the digital library. This model incorporated two new features that determine the right third-party source services. It also offers an opportunity for further investigation for evaluating the service quality effectiveness in the digital library. It is conforming to the study backgrounds through a variety of research designs and settings by examination of the hypotheses presented in this study. Survey research designs employing third party sources services as a sample in the model would best match the requirements for validating the proposed framework. The result shows that all three hypotheses are supported. As a result, we propose a conceptual model for evaluating the service quality of the digital library and further analyze the effectiveness model with several contributing features grouped as a thirdparty source.

It is commonly accepted that scientific research or, more precisely, the number of scientific publications, in computer science has greatly increased over the last few years. The reason would appear to be the pressure to publish, coined by the expression "Publish or perish", which is, among other things, necessary for promotions and applications for grants or projects. In this paper we have conducted a study that covers computer science publications from 1936 to 2010 in order to quantify this increase in publications regarding computing research. We have considered the computing conferences and journals available in the DBLP computer science bibliography (DBLP 2013) database, including more than 1.5 million papers, and more than 4 million authors (more than 900,000 different people), corresponding to about 1,000 different journals and 3,000 different conferences and workshops. Our study confirms and quantifies these increases with regard to the number of papers, number of authors, number of papers per author, etc. However, it also reaches a surprising conclusion: the real productivity of researchers has decreased throughout history. The reason for this decrease is the average number of authors per paper, which has grown significantly and is currently three.

Extraction of temporal relations from clinical free text: A systematic review of current approaches.