DNS-embedded service endpoint registry for distributed e-Infrastructures

Distributed e-Infrastructure is a key component of modern BIG Science. Service discovery in e-Science environments, such as Worldwide LHC Computing Grid (WLCG), is a crucial functionality that relies on service registry. In this paper we re-formulate the requirements for the service endpoint registry based on our more than 10 years experience with many systems designed or used within the WLCG e-Infrastructure. To satisfy those requirements the paper proposes a novel idea to use the existing well-established Domain Name System (DNS) infrastructure together with a suitable data model as a service endpoint registry. The presented ARC Hierarchical Endpoints Registry (ARCHERY) system consists of a minimalistic data model representing services and their endpoints within e-Infrastructures, a rendering of the data model embedded into DNS-records, a lightweight software layer for DNS-record management and client-side data discovery. Our approach for the ARCHERY registry required minimal software development and inherits all the benefits of one of the most reliable distributed information discovery source of the internet, the DNS infrastructure. In particular, deployment, management and operation of ARCHERY is fully relying on DNS. Results of ARCHERY deployment use-cases are provided together with performance analysis.

Serendipity in human information behavior: a systematic review

PurposeSerendipitous information discovery has become a unique and important approach to discovering and obtaining information, which has aroused a growing interest for serendipity in human information behavior. Despite numerous publications, few have systematically provided an overview of current state of serendipity research. Consequently, researchers and practitioners are less able to make effective use of existing achievements, which limits them from making advancements in this domain. Against this backdrop, we performed a systematic literature review to explore the world of serendipity and to recapitulate the current states of different research topics.Design/methodology/approachGuided by a prior designed review protocol, this paper conducted both automatic and manual search for available studies published from January 1990 to December 2020 on seven databases. A total of 207 serendipity studies closely related to human information behavior form the literature pool.FindingsWe provide an overview of distinct aspects of serendipity, that is research topics, potential benefits, related concepts, theoretical models, contextual factors and data collection methods. Based on these findings, this review reveals limitations and gaps in the current serendipity research and proposes an agenda for future research directions.Originality/valueBy analyzing current serendipity research, developing a knowledge framework and providing a research agenda, this review is of significance for researchers who want to find new research questions or re-align current work, for beginners who need to quickly understand serendipity, and for practitioners who seek to cultivate serendipity in information environments.

ENHANCED APPROACH FOR SOIL CLASSIFICATION USING BOOSTED C5.0 DECISION TREE ALGORITHM

Data mining includes the utilization of erudite data analysis tools to discover previously unidentified, suitable patterns and relationships in enormous data sets. Data mining tools can incorporate statistical models, machine learning methods such as neural networks or decision trees, and mathematical algorithms. As a result data mining comprises of more process. This performs analysis and prediction than collecting and managing data. The main objective of data mining is to identify valid, potentially useful, novel and understandable correlations and patterns in existing data. Finding and analyzing useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archaeology, and data pattern processing). The term data mining is basically utilized by statisticians, database researchers, and the business communities.

Soluciones de arquitectura de la información en plataformas digitales editoriales: revisión comparativa de Taylor and Francis Online, SAGE Journals, PLOS One, MDPI y Open Research Europe

Digital publishing platforms are complex academic communication systems that must incorporate information architecture solutions to enable content access at various levels, including the whole publication and each individual article. In addition, to truly harness the advantages offered by the digital world, such platforms must also offer information discovery functions as well as access to information. The former can be implemented by using hypertextuality and, more specifically, links based on semantic similarity. We present herein a review of the various solutions provided in these regards by five important digital platforms. Resumen Las plataformas digitales editoriales son complejos sistemas de comunicación académica que deben incorporar soluciones de arquitecturas de la información para diversos niveles de acceso a los contenidos. Entre tales niveles destacan el de la publicación como un todo, y el de cada artículo individual. Además, para potenciar las genuinas propiedades del mundo digital, estas plataformas deben ofrecer funciones de descubrimiento de la información, y no solamente de acceso. Las primeras pueden implementarse gracias a la hipertextualidad y, más en concreto, gracias a enlaces basados en semejanza semántica. En este trabajo presentamos una revisión de las diferentes soluciones aportadas en estos elementos por cinco plataformas digitales de gran significación.

Using computational tools to support journalists’ creativity

This paper presents work surrounding INJECT, a newsroom innovation offering digital tools to support journalists. Research showing increasing time and resource pressure on journalists has led to concerns about the demise of investigative reporting and the ability of today’s journalists to interrogate information adequately. Some digital innovations (e.g. tools facilitating robot journalism) have been viewed with suspicion by newsrooms. This paper reports on a research project that seeks to create an innovative tool to support the creative capabilities of time and resource poor journalists. The INJECT project used the advanced information discovery capabilities of digitisation to help journalists find new angles on stories and this paper analyses the extent to which such initiatives might harness digital innovation to benefit both the quality and range of reporting and thereby enhance creativity. It examines the potential of an information processing model of creativity derived from the INJECT tool to assist and support journalists, exploring the theoretical impact as well as the practical implications reported from the newsroom.