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Developing sustainable software solutions for bioinformatics by the " Butterfly" paradigm.

Ahmed Z, Zeeshan S, Dandekar T - F1000Res (2014)

Bottom Line: User feedback is valued as well as software planning in a sustainable and interoperable way.A middleware supports a user-friendly Graphical User Interface (GUI) as well as a database/tool development independently.We validated the approach of our own software development and compared the different design paradigms in various software solutions.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurobiology and Genetics, Biocenter, University of Wuerzburg, Wuerzburg, 97074, Germany ; Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, 97074, Germany.

ABSTRACT
Software design and sustainable software engineering are essential for the long-term development of bioinformatics software. Typical challenges in an academic environment are short-term contracts, island solutions, pragmatic approaches and loose documentation. Upcoming new challenges are big data, complex data sets, software compatibility and rapid changes in data representation. Our approach to cope with these challenges consists of iterative intertwined cycles of development (" Butterfly" paradigm) for key steps in scientific software engineering. User feedback is valued as well as software planning in a sustainable and interoperable way. Tool usage should be easy and intuitive. A middleware supports a user-friendly Graphical User Interface (GUI) as well as a database/tool development independently. We validated the approach of our own software development and compared the different design paradigms in various software solutions.

No MeSH data available.


Scientific software solution planning.Abstract planning is the first step of the top, abstract layer (gray,Figure 4) of the Butterfly design, key steps are indicated.
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f5: Scientific software solution planning.Abstract planning is the first step of the top, abstract layer (gray,Figure 4) of the Butterfly design, key steps are indicated.

Mentions: Scientific software solution planning (Figure 5) is the first step towards a new scientific application development, which requires the introduction to the field itself (e.g. biochemistry, neurobiology, genetics, metabolomics, proteomicsetc.) and project related information (e.g. what could be the end product, input to the system, expected output from the system, methodology, ideas, opinionsetc.). It is important to know about the user’s information IT background and existing already available (old and recently developed) scientific solutions to the problem. The next important phase is to perform requirements engineering and analysis (Figure 6). During this phase, the most important tasks are to gather the requirements from users (e.g. interviews, brainstorming, documents, publications, running related systems based informationetc.) and classify the information in functional and non-functional categories. Here, function requirements are those which can be implemented (based on existing resources, time, budget, labor, tools, technologies and methodologies), and non-functional requirements are those which cannot be implemented. It is very important to clarify with the users what will be the expected end-product because it is possible that the user may not like the output of the system after development. In this case, all the efforts will have been in vain.


Developing sustainable software solutions for bioinformatics by the " Butterfly" paradigm.

Ahmed Z, Zeeshan S, Dandekar T - F1000Res (2014)

Scientific software solution planning.Abstract planning is the first step of the top, abstract layer (gray,Figure 4) of the Butterfly design, key steps are indicated.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4215756&req=5

f5: Scientific software solution planning.Abstract planning is the first step of the top, abstract layer (gray,Figure 4) of the Butterfly design, key steps are indicated.
Mentions: Scientific software solution planning (Figure 5) is the first step towards a new scientific application development, which requires the introduction to the field itself (e.g. biochemistry, neurobiology, genetics, metabolomics, proteomicsetc.) and project related information (e.g. what could be the end product, input to the system, expected output from the system, methodology, ideas, opinionsetc.). It is important to know about the user’s information IT background and existing already available (old and recently developed) scientific solutions to the problem. The next important phase is to perform requirements engineering and analysis (Figure 6). During this phase, the most important tasks are to gather the requirements from users (e.g. interviews, brainstorming, documents, publications, running related systems based informationetc.) and classify the information in functional and non-functional categories. Here, function requirements are those which can be implemented (based on existing resources, time, budget, labor, tools, technologies and methodologies), and non-functional requirements are those which cannot be implemented. It is very important to clarify with the users what will be the expected end-product because it is possible that the user may not like the output of the system after development. In this case, all the efforts will have been in vain.

Bottom Line: User feedback is valued as well as software planning in a sustainable and interoperable way.A middleware supports a user-friendly Graphical User Interface (GUI) as well as a database/tool development independently.We validated the approach of our own software development and compared the different design paradigms in various software solutions.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurobiology and Genetics, Biocenter, University of Wuerzburg, Wuerzburg, 97074, Germany ; Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, 97074, Germany.

ABSTRACT
Software design and sustainable software engineering are essential for the long-term development of bioinformatics software. Typical challenges in an academic environment are short-term contracts, island solutions, pragmatic approaches and loose documentation. Upcoming new challenges are big data, complex data sets, software compatibility and rapid changes in data representation. Our approach to cope with these challenges consists of iterative intertwined cycles of development (" Butterfly" paradigm) for key steps in scientific software engineering. User feedback is valued as well as software planning in a sustainable and interoperable way. Tool usage should be easy and intuitive. A middleware supports a user-friendly Graphical User Interface (GUI) as well as a database/tool development independently. We validated the approach of our own software development and compared the different design paradigms in various software solutions.

No MeSH data available.