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Data Science - Volume 5, issue 1

open access

Open Access
ISSN 2451-8484 (P)
ISSN  2451-8492 (E)

The journal Data Science is an interdisciplinary journal that aims to publish novel and effective methods on using scientific data in a principled, well-defined, and reproducible fashion, concrete tools that are based on these methods, and applications thereof. The ultimate goal is to unleash the power of scientific data to deepen our understanding of physical, biological, and digital systems, gain insight into human social and economic behavior, and design new solutions for the future. The rising importance of scientific data, both big and small, brings with it a wealth of challenges to combine structured, but often siloed data with messy, incomplete, and unstructured data from text, audio, visual content such as sensor and weblog data. New methods to extract, transport, pool, refine, store, analyze, and visualize data are needed to unleash their power while simultaneously making tools and workflows easier to use by the public at large. The journal invites contributions ranging from theoretical and foundational research, platforms, methods, applications, and tools in all areas. We welcome papers which add a social, geographical, and temporal dimension to Data Science research, as well as application-oriented papers that prepare and use data in discovery research.

Core Topics

This journal focuses on methods, infrastructure, and applications around the following core topics:

  • - scientific data mining, machine learning, and Big Data analytics
  • - data management, network analysis, and scientific knowledge discovery
  • - scholarly communication and (semantic) publishing
  • - research data publication, indexing, quality, and discovery
  • - data wrangling, integration, provenance
  • - trend analysis, prediction, and visualization
  • - crowdsourcing and collaboration
  • - corroboration, validation, trust, and reproducibility
  • - scalable computing, analysis, and learning
  • - smart and semantic web services, executable workflows
  • - analytics, intelligence, and real time decision making
  • - socio-technical systems
  • - social impacts of data science

Features

Semantic Publishing

Semantic publishing has been defined as anything that enhances the meaning of a published journal article, facilitates its automated discovery, enables its linking to semantically related articles, provides access to data within the article in actionable form, or facilitates integration of data between papers. Towards the goal of genuine semantic publishing, where a work may be published with its content and metadata represented in a machine-interpretable semantic notation, this journal will work with a global set of partners to develop standardized methods to ensure that our publications can be seen as a machine-accessible store of knowledge.

Data Standards

An important goal of the journal is to promote an environment to produce and share annotated data to the wider research community. The development and use of data and metadata standards are critical for achieving this goal. Authors should ensure that any data used or produced in the study is represented with community-based data formats and metadata standards.

Rapid, Open, Transparent, and Attributed Reviews

The Data Science journal relies on an open and transparent review process. Submitted manuscripts are posted on the journal’s website and are publicly available. In addition to solicited reviews selected by members of the editorial board, public reviews and comments are welcome by any researcher and can be uploaded using the journal website. All reviews and responses from the authors are posted on the journal homepage. All involved reviewers and editors will be acknowledged in the final printed version. While we strongly encourage reviewers to participate in the open and transparent review process, it is still possible to submit anonymous reviews. Editors, non-anonymous reviewers will be included in all published articles. The journal will aim to complete reviews within 2-4 weeks of submission.

Reviewer Forum

The journal will provide editor and reviewer profiles and metrics (links to ORCID, Google Scholar, etc.).

Open Access

The journal will be open access.
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Special Issue on Semantic Publishing with Formalization Papers

Authors: Bucur, Cristina-Iulia | Kuhn, Tobias

Article Type: Editorial

DOI: 10.3233/DS-220055

Citation: Data Science, vol. 5, no. 1, pp. 1-9, 2022

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A formalization of one of the main claims of “FTO Obesity Variant Circuitry and Adipocyte Browning in Humans” by Claussnitzer et al. 2015

Authors: Joslin, Amelia

Article Type: Formalization Paper

Abstract: Claussnitzer et al. claimed in previous work that a regulatory element within the first intron of FTO affects IRX3 and IRX5 expression during early adipogenesis. We present here a formalization of that claim, stating that all things of class “early human adipogenesis” that are in the context of a thing of class “regulatory element within the first intron of FTO” generally have a relation of type “affects” to a thing of class “expression of genes IRX3 and IRX5” in the same context.

Keywords: Early human adipogenesis, regulatory element within the first intron of FTO, expression of genes IRX3 and IRX5

DOI: 10.3233/DS-210038

Citation: Data Science, vol. 5, no. 1, pp. 11-15, 2022

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A formalization of one of the main claims of “ALS-implicated protein TDP-43 sustains levels of STMN2, a mediator of motor neuron growth and repair” by Klim et al. 2019

Authors: Nichols, B. Nolan

Article Type: Formalization Paper

Abstract: Klim et al. claimed in previous work that the protein TDP-43 generally contributes to the transcription of STMN2 in human motor neurons. We present here a formalization of that claim, stating that all things of class “TAR DNA binding protein” that are in the context of a thing of class “human motor neuron” can generally have a relation of type “contributes to” to a thing of class “transcription of stmn2” in the same context.

Keywords: Human motor neuron, TAR DNA binding protein, transcription of stmn2

DOI: 10.3233/DS-210039

Citation: Data Science, vol. 5, no. 1, pp. 17-19, 2022

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A formalization of one of the main claims of “Cortex reorganization of Xenopus laevis eggs in strong static magnetic fields” by Mietchen et al. 2005

Authors: Mietchen, Daniel

Article Type: Formalization Paper

Abstract: Mietchen et al. claimed in previous work that strong static magnetic fields change the cell cortex in dejellied fertilizable stage VI Xenopus lavis oocytes. We present here a formalization of that claim, stating that all things of class “strong static magnetic field” that are in the context of a thing of class “dejellied fertilizable stage VI Xenopus laevis oocyte” generally have a relation of type “affects” to a thing of class “cell cortex” in the same context.

Keywords: Dejellied fertilizable stage VI Xenopus laevis oocyte, strong static magnetic field, cell cortex

DOI: 10.3233/DS-210040

Citation: Data Science, vol. 5, no. 1, pp. 21-23, 2022

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A formalization of one of the main claims of “Overlap of vitamin A and vitamin D target genes with CAKUT-related processes” by Ozisik et al. 2021

Authors: Ehrhart, Friederike | Evelo, Chris T.

Article Type: Formalization Paper

Abstract: In a previous paper that we co-authored (Ozisik et al. 2021) we showed that in some cases Vitamin A and Vitamin D receptor binding sites are present in genes associated with Congenital Anomalies of the Kidney and Urinary Tract (CAKUT). From that finding we derived the statement that sometimes Vitamin A targets are the same as genes associated with CAKUT. We present here a formalization of that claim, stating that all things of class “genes associated with CAKUT” sometimes have a relation of type “is same as” to a thing of class “targets of vitamin A”.

Keywords: Genes associated with CAKUT, targets of vitamin A

DOI: 10.3233/DS-210041

Citation: Data Science, vol. 5, no. 1, pp. 25-27, 2022

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A formalization of one of the main claims of “Cost-effectiveness analysis of pharmacogenomics-guided clopidogrel treatment in Spanish patients undergoing percutaneous coronary intervention” by Fragoul…

Authors: Patrinos, George P.

Article Type: Formalization Paper

Abstract: Fragoulakis et al. claimed in previous work that pharmacogenomics-guided clopidogrel strategy represents a cost-effective treatment for patients undergoing PCI. We present here a formalization of that claim, stating that all things of class “pharmacogenomics guided clopidogrel therapy” that are in the context of a thing of class “patient undergoing PCI” generally have a relation of type “enables” to a thing of class “cost-effective treatment” in the same context.

Keywords: Patient undergoing PCI, pharmacogenomics-guided clopidogrel therapy, cost-effective treatment

DOI: 10.3233/DS-210042

Citation: Data Science, vol. 5, no. 1, pp. 29-33, 2022

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A formalization of one of the main claims of “Sonic hedgehog signaling in astrocytes” by Hill et al. 2021

Authors: Martorana, Margherita

Article Type: Formalization Paper

Abstract: Hill et al. claimed in previous work that sonic hedgehog signalling pathway is an essential regulator of astrocytes development. We present here a formalization of that claim, stating that all things of class “smoothened signaling pathway” that are in the context of a thing of class “human” mostly have a relation of type “affects” to a thing of class “astrocyte development” in the same context.

Keywords: Human, smoothened signaling pathway, astrocyte development

DOI: 10.3233/DS-210043

Citation: Data Science, vol. 5, no. 1, pp. 35-37, 2022

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A formalization of one of the main claims of “Creative Commons licenses and the non-commercial condition: Implications for the re-use of biodiversity information” by Hagedorn et al. 2011

Authors: Mietchen, Daniel | Penev, Lyubomir | Dimitrova, Mariya

Article Type: Formalization Paper

Abstract: Hagedorn et al. claimed in previous work that when talking about biodiversity data, licenses with a non-commercial clause generally inhibit data reuse. We present here a formalization of that claim, stating that all things of class “license with non-commercial clause” that are in the context of a thing of class “biodiversity data” generally have a relation of type “inhibits” to a thing of class “data reuse” in the same context.

Keywords: Biodiversity data, license with non-commercial clause, data reuse

DOI: 10.3233/DS-210044

Citation: Data Science, vol. 5, no. 1, pp. 39-42, 2022

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A formalization of one of the main claims of “OpenBiodiv: A knowledge graph for literature-extracted linked open data in biodiversity science” by Penev et al. 2019

Authors: Dimitrova, Mariya

Article Type: Formalization Paper

Abstract: Penev et al. claimed in previous work that triples in the OpenBiodiv knowledge graph releases are generally semantic triples extracted from biodiversity literature. We present here a formalization of that claim, stating that all things of class “triple in OpenBiodiv knowledge graph” that are in the context of a thing of class “release of OpenBiodiv knowledge graph” generally have a relation of type “is same as” to a thing of class “semantic triple extracted from biodiversity literature” in the same context.

Keywords: release of OpenBiodiv knowledge graph, triple in OpenBiodiv knowledge graph, semantic triple extracted from biodiversity literature

DOI: 10.3233/DS-210045

Citation: Data Science, vol. 5, no. 1, pp. 43-47, 2022

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A formalization of one of the main claims of “TDP-43 represses cryptic exon inclusion in FTD/ALS gene UNC13A” by Rosa Ma et al. 2021

Authors: Brauer, Matthew

Article Type: Formalization Paper

Abstract: Rosa Ma et al. claimed in previous work that the protein TDP-43 represses cryptic exon inclusion in the gene UNC13A. We present here a formalization of that claim, stating that all things of class “TAR DNA binding protein” that are in the context of a thing of class “UNC13A” generally have a relation of type “inhibits” to a thing of class “inclusion of cryptic exon” in the same context.

Keywords: UNC13A, TAR DNA binding protein, inclusion of cryptic exon

DOI: 10.3233/DS-210046

Citation: Data Science, vol. 5, no. 1, pp. 49-51, 2022

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