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Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

ABSTRACT: We define a software ecosystem as a set of organizations collaboratively serving a market for software and services. Typically these ecosystems are underpinned by a common technology, such as an extendable software platform. This data set supports the article that describes the Software Ecosystem Governance Maturity Model ( SEG-M2 ) [50]. The model has the goal to support software ecosystem orchestrators in the management and governance of the actors in their ecosystems in a structured way. Through a critical structured literature review, 168 practices have been collected. These practices have been evaluated through six case studies at software ecosystem orchestrators. The practices are described with a practice code, a practice name, a practice description, required success conditions, the person responsible for the practice, and the associated literature where the practice was identified.

SUBMITTER: Jansen S

PROVIDER: S-EPMC7256292 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

Jansen Slinger S Yang Zherui Z

Data in brief 20200512

We define a software ecosystem as a set of organizations collaboratively serving a market for software and services. Typically these ecosystems are underpinned by a common technology, such as an extendable software platform. This data set supports the article that describes the Software Ecosystem Governance Maturity Model ( SEG-M2 ) [50]. The model has the goal to support software ecosystem orchestrators in the management and governance of the actors in their ecosystems in a structured way. Thro ...[more]

PMID: 32490064

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Project description:In order that biological meaning may be derived and testable hypotheses may be built from proteomics experiments, assignments of proteins identified by mass spectrometry or other techniques must be supplemented with additional notation, such as information on known protein functions, protein-protein interactions, or biological pathway associations. Collecting, organizing, and interpreting this data often requires the input of experts in the biological field of study, in addition to the time-consuming search for and compilation of information from online protein databases. Furthermore, visualizing this bulk of information can be challenging due to the limited availability of easy-to-use and freely available tools for this process. In response to these constraints, we have undertaken the design of software to automate annotation and visualization of proteomics data in order to accelerate the pace of research. Here we present the Software Tool for Researching Annotations of Proteins (STRAP), a user-friendly, open-source C# application. STRAP automatically obtains gene ontology (GO) terms associated with proteins in a proteomics results ID list using the freely accessible UniProtKB and EBI GOA databases. Summarized in an easy-to-navigate tabular format, STRAP results include meta-information on the protein in addition to complementary GO terminology. Additionally, this information can be edited by the user so that in-house expertise on particular proteins may be integrated into the larger data set. STRAP provides a sortable tabular view for all terms, as well as graphical representations of GO-term association data in pie charts (biological process, cellular component, and molecular function) and bar charts (cross comparison of sample sets) to aid in the interpretation of large data sets and differential analyses experiments. Furthermore, proteins of interest may be exported as a unique FASTA-formatted file to allow for customizable re-searching of mass spectrometry data, and gene names corresponding to the proteins in the lists may be encoded in the Gaggle microformat for further characterization, including pathway analysis. STRAP, a tutorial, and the C# source code are freely available from http://cpctools.sourceforge.net.

Dataset Information

Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

Publications

Source Data for the Focus Area Maturity Model for Software Ecosystem Governance.

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