Introductory Information

Introductory information, including the editorial advisory board and the editorial policy

Introductory Information

Introductory information about the publication, including the editorial advisory board and the editorial policy

Introductory Information and Introduction

Introductory information, including the editorial policy and editorial advisory board, and the editor\u27s introduction to the issue

Introductory Information and Introduction

Introductory information, such as the editorial policy and the editorial advisory board, and the editor\u27s introduction for this issue

Introduction

Introductory information about the publication, including the editorial advisory board and editorial policy, with an introduction to the volume by the editor

Introductory Editorial

The Open Journal of Databases (OJDB) is a new open access journal covering all aspects of database research and technology. In this editorial, the first issue of the journal is presented

Introductory Editorial

The Open Journal of Information Systems is a new open-access journal covering all aspects of information systems. In this introductory issue, we present two articles. In the first article, Kessler et al. present new techniques to achieve better anonymity in time series. In the second article, Iivari introduces a new model from which we can derive recommendations to improve the use of social network services

Introductory Editorial

The Open Journal of Big Data is a new open access journal published by RonPub, and RonPub is an academic publisher of online, open access, peer-reviewed journals. OJBD addresses aspects of Big Data, including new methodologies, processes, case studies, poofs-of-concept, scientific demonstrations, industrial applications and adoption. This editorial presents the two articles in this first issue. The first paper is on An Efficient Approach for Cost Optimization of the Movement of Big Data, which mainly focuses on the challenge of moving big data from one data center to other.The second paper is on Cognitive Spam Recognition Using Hadoop and Multicast-Update, which describes a method to make machines cognitively label spam using Machine Learning and the Naive Bayesian approach. OJBD has a rising reputation thanks to the support of research communities, which help us set up the First International Conference on Internet of Things and Big Data 2016 (IoTBD 2016), in Rome, Italy, between 23 and 25 April 2016