Distributed and Parallel Databases

Top Research Topics at Distributed and Parallel Databases?

The journal primarily tackles Data structure, Distributed computing, Data mining, Database and Theoretical computer science. In Distributed and Parallel Databases, Scalability, Distributed database, Set (abstract data type), Algorithm and Big data are investigated in conjunction with one another to address concerns in Data structure research. It holds forums on Distributed computing that merges themes from other disciplines such as Database transaction, Query optimization, Scheduling (computing), Cloud computing and Distributed transaction.

While Query optimization is the focus of it, it also provided insights into the studies of Web search query and View. Topics in Web search query explored in Distributed and Parallel Databases were investigated in conjunction with research in Query language and Query expansion. It covers Distributed transaction research under the subject of Transaction processing.

Research on Data mining addressed in it frequently intersections with the field of Cluster analysis.

• Data structure (64.30%)
• Distributed computing (24.78%)
• Data mining (17.16%)

What are the most cited papers published in the journal?

• An overview of workflow management: from process modeling to workflow automation infrastructure (1501 citations)
• Real-time databases (532 citations)
• OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Pre-Existing Ontologies (488 citations)

Research areas of the most cited articles at Distributed and Parallel Databases:

The main points discussed in the journal papers deal with Data structure, Database, Distributed computing, Data mining and Workflow. While work presented in the published articles provide substantial information on Data structure, it also covers topics in Theoretical computer science, Data integration, Information retrieval, Search engine indexing and Data science. The published articles explore Workflow concepts, specifically Workflow technology but expand to research in Teamwork.

What topics the last edition of the journal is best known for?

• Operating system
• Database
• Artificial intelligence

The previous edition focused in particular on these issues:

Distributed and Parallel Databases facilitates discussions on Data structure, Artificial intelligence, Algorithm, Cloud computing and Data mining. Some problems in Data structure that were presented in Distributed and Parallel Databases overlapped with concepts under Parallel processing (DSP implementation), Set (abstract data type), Cluster analysis, Data stream mining and Big data. Distributed and Parallel Databases focuses on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning, Computer vision and Pattern recognition.

Algorithm research featured in Distributed and Parallel Databases incorporates concerns from various other topics such as Sliding window protocol, Throughput (business) and Genetic algorithm. The research on Cloud computing tackled can also make contributions to studies in the areas of Resource (project management), Distributed computing, Encryption and The Internet. Distributed and Parallel Databases facilitates discussions on Distributed computing that incorporate concepts from other fields like Scheduling (computing) and Task (computing).

The most cited articles from the last journal are:

• Holistic evaluation in multi-model databases benchmarking (8 citations)
• Stratified random sampling from streaming and stored data (3 citations)
• An improved query optimization process in big data using ACO-GA algorithm and HDFS map reduce technique (3 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Distributed and Parallel Databases (based on the number of publications) are:

• Patrick Valduriez (12 papers) published 1 paper at the last edition the same number as at the previous edition,
• Divyakant Agrawal (11 papers) absent at the last edition,
• Amit P. Sheth (10 papers) absent at the last edition,
• Sanjay Kumar Madria (9 papers) absent at the last edition,
• Panos K. Chrysanthis (7 papers) published 1 paper at the last edition the same number as at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Distributed and Parallel Databases (based on the number of publications) are:

• IBM (21 papers) published 1 paper at the last edition,
• French Institute for Research in Computer Science and Automation (17 papers) absent at the last edition,
• Purdue University (14 papers) absent at the last edition,
• University of California, Santa Barbara (11 papers) absent at the last edition,
• Hong Kong University of Science and Technology (11 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 15.28% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 4.92% were posted by at least one author from the top 10 institutions publishing in the journal. Another 3.28% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 9.84% of all publications and 81.97% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

How To Get Published in Distributed and Parallel Databases

For budding authors looking to publish their articles in Distributed and Parallel Databases, the following steps can guide you: - Firstly, ensure your research falls in line with the core subjects majorly explored in the journal; this includes Data Structure, Distributed Computing, Data Mining, etc. - Then, check the quality of your work: This journal features articles that make remarkable contributions to their respective fields, with some having plentiful citations. Such quality in your work would improve your chances of getting published. - Subsequently, you need to adhere to the journal's stipulated guidelines for submission. This might require you to present your work in a distinct format or style. - Lastly, it is advisable to familiarize yourself with research previously published in the journal. This can give you a sense of the kind of contributions they value and how to align your work accordingly. On an interesting side note, this process might be similar to how you might prepare for a career in education - refining your skills and knowledge, adhering to set guidelines, familiarizing yourself with pre-existing work in the field, etc. Those looking to venture down this path can learn more about how to become a teacher in Tennessee with a bachelor's degree.