Transformation and Impact from the Software Ecosystem Perspective: Case Study of Autodesk Inc.'s Ecosystem Roadmap

2021 ◽  
Author(s):  
James K. C. Chen ◽  
Han-Hsi Ho
Keyword(s):  
Software Ecosystem

scholarly journals BioKEEN: a library for learning and evaluating biological knowledge graph embeddings

2019 ◽  
Vol 35 (18) ◽  
pp. 3538-3540 ◽  
Author(s):  
Mehdi Ali ◽  
Charles Tapley Hoyt ◽  
Daniel Domingo-Fernández ◽  
Jens Lehmann ◽  
Hajira Jabeen
Keyword(s):  
Supplementary Information ◽  
Knowledge Graph ◽  
Biological Knowledge ◽  
Command Line ◽  
Graph Embeddings ◽  
Command Line Interface ◽  
Software Ecosystem ◽  
Mapping Resource ◽  
Significant Attention

Abstract Summary Knowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem for their application to bioinformatics remains limited and inaccessible for users without expertise in programing and machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs) to facilitate their easy use through an interactive command line interface. Finally, we present a case study in which we used a novel biological pathway mapping resource to predict links that represent pathway crosstalks and hierarchies. Availability and implementation BioKEEN and PyKEEN are open source Python packages publicly available under the MIT License at https://github.com/SmartDataAnalytics/BioKEEN and https://github.com/SmartDataAnalytics/PyKEEN Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

2018 ◽  
Author(s):  
Mehdi Ali ◽  
Charles Tapley Hoyt ◽  
Daniel Domingo-Fernández ◽  
Jens Lehmann ◽  
Hajira Jabeen
Keyword(s):  
Knowledge Graph ◽  
Biological Knowledge ◽  
Command Line ◽  
Graph Embeddings ◽  
Command Line Interface ◽  
Software Ecosystem ◽  
Link Type ◽  
Mapping Resource ◽  
Significant Attention

AbstractKnowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem for their application to bioinformatics remains limited and inaccessible for users without expertise in programming and machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs) to facilitate their easy use through an interactive command line interface. Finally, we present a case study in which we used a novel biological pathway mapping resource to predict links that represent pathway crosstalks and hierarchies.AvailabilityBioKEEN and PyKEEN are open source Python packages publicly available under the MIT License at https://github.com/SmartDataAnalytics/BioKEEN and https://github.com/SmartDataAnalytics/PyKEEN as well as through PyPI.

scholarly journals Phylogenetic analysis of software evolution, a case study: VE&MINT

2018 ◽  
Author(s):  
Alvaro Ortiz-Troncoso
Keyword(s):  
Phylogenetic Analysis ◽  
Life Cycle ◽  
Open Source ◽  
Software Evolution ◽  
Real Life ◽  
Traditional View ◽  
Software Ecosystem ◽  
Life Project ◽  
Project Governance

Open source projects may face a forking situation at some point during their life-cycle. The traditional view is that forks are a waste of project resources and should be avoided. However, in a wider technological and organisational context, forks can be a way to foster the creation of a software ecosystem. Either way, forking is explicitly allowed by open source licenses. Notwithstanding, methods for quantifying the evolution of forks are currently scarce. The present work attempts to answer the question whether a real-life project has forked. It does so by considering code and organisational characteristics of the project, and analysing these characteristics by applying methods ported from biological phylogenetics. After finding that the project is forked, implications for project governance are discussed.

Bridges and barriers to hardware-dependent software ecosystem participation – A case study

2014 ◽  
Vol 56 (11) ◽  
pp. 1493-1507 ◽  
Author(s):  
Krzysztof Wnuk ◽  
Per Runeson ◽  
Matilda Lantz ◽  
Oskar Weijden
Keyword(s):  
Software Ecosystem

scholarly journals Phylogenetic analysis of software evolution, a case study: VE&MINT

2018 ◽  
Author(s):  
Alvaro Ortiz-Troncoso
Keyword(s):  
Phylogenetic Analysis ◽  
Life Cycle ◽  
Open Source ◽  
Software Evolution ◽  
Real Life ◽  
Traditional View ◽  
Software Ecosystem ◽  
Life Project ◽  
Project Governance

Open source projects may face a forking situation at some point during their life-cycle. The traditional view is that forks are a waste of project resources and should be avoided. However, in a wider technological and organisational context, forks can be a way to foster the creation of a software ecosystem. Either way, forking is explicitly allowed by open source licenses. Notwithstanding, methods for quantifying the evolution of forks are currently scarce. The present work attempts to answer the question whether a real-life project has forked. It does so by considering code and organisational characteristics of the project, and analysing these characteristics by applying methods ported from biological phylogenetics. After finding that the project is forked, implications for project governance are discussed.

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