IDEAS home Printed from https://ideas.repec.org/a/eee/ininma/v46y2019icp124-141.html
   My bibliography  Save this article

Developing a government enterprise architecture framework to support the requirements of big and open linked data with the use of cloud computing

Author

Listed:
  • Lnenicka, Martin
  • Komarkova, Jitka

Abstract

Governmental and local authorities are facing many new information and communication technologies challenges. The amount of data is rapidly increasing. The data sets are published in different formats. New services are based on linking and processing differently structured data from various sources. Users expect openness of public data, fast processing, and intuitive visualisation. The article addresses the challenges and proposes a new government enterprise architecture framework. The following partial architectures are included: big and open linked data storage, processing, and publishing using cloud computing. At first, the key concepts are defined. Next, the basic architectural roles and components are specified. The components result from the decomposition of related frameworks. The main part of the article deals with the detailed proposal of the architecture framework and partial views on architecture (sub-architectures). A methodology, including a proposal of appropriate steps, solutions and responsibilities for them, is described in the next step - after the verification and validation of the new framework with respect to the attributes of quality. The new framework responds to emerging ICT trends in order to evolve government enterprise architecture continually and represent current architectural components and their relationships.

Suggested Citation

  • Lnenicka, Martin & Komarkova, Jitka, 2019. "Developing a government enterprise architecture framework to support the requirements of big and open linked data with the use of cloud computing," International Journal of Information Management, Elsevier, vol. 46(C), pages 124-141.
    • Handle: RePEc:eee:ininma:v:46:y:2019:i:c:p:124-141
    DOI: 10.1016/j.ijinfomgt.2018.12.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0268401218305942
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijinfomgt.2018.12.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yogesh K. Dwivedi & Marijn Janssen & Emma L. Slade & Nripendra P. Rana & Vishanth Weerakkody & Jeremy Millard & Jan Hidders & Dhoya Snijders, 2017. "Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling," Information Systems Frontiers, Springer, vol. 19(2), pages 197-212, April.
    2. Yogesh K. Dwivedi & Marijn Janssen & Emma L. Slade & Nripendra P. Rana & Vishanth Weerakkody & Jeremy Millard & Jan Hidders & Dhoya Snijders, 0. "Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    3. Kamal, Muhammad Mustafa & Hackney, Ray & Ali, Maged, 2013. "Facilitating enterprise application integration adoption: An empirical analysis of UK local government authorities," International Journal of Information Management, Elsevier, vol. 33(1), pages 61-75.
    4. Jallow, Abdou Karim & Demian, Peter & Anumba, Chimay J. & Baldwin, Andrew N., 2017. "An enterprise architecture framework for electronic requirements information management," International Journal of Information Management, Elsevier, vol. 37(5), pages 455-472.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    2. Maciej Grzenda & Jaroslaw Legierski, 2021. "Towards Increased Understanding of Open Data Use for Software Development," Information Systems Frontiers, Springer, vol. 23(2), pages 495-513, April.
    3. Morteza Ghobakhloo & Mohammad Iranmanesh & Andrius Grybauskas & Mantas Vilkas & Monika Petraitė, 2021. "Industry 4.0, innovation, and sustainable development: A systematic review and a roadmap to sustainable innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 30(8), pages 4237-4257, December.
    4. Shivam Gupta & Vinayak A. Drave & Surajit Bag & Zongwei Luo, 2019. "Leveraging Smart Supply Chain and Information System Agility for Supply Chain Flexibility," Information Systems Frontiers, Springer, vol. 21(3), pages 547-564, June.
    5. Federico Cabitza & Angela Locoro & Carlo Batini, 2020. "Making Open Data more Personal Through a Social Value Perspective: a Methodological Approach," Information Systems Frontiers, Springer, vol. 22(1), pages 131-148, February.
    6. Marijn Janssen & David Konopnicki & Jane L. Snowdon & Adegboyega Ojo, 2017. "Driving public sector innovation using big and open linked data (BOLD)," Information Systems Frontiers, Springer, vol. 19(2), pages 189-195, April.
    7. Marijn Janssen & David Konopnicki & Jane L. Snowdon & Adegboyega Ojo, 0. "Driving public sector innovation using big and open linked data (BOLD)," Information Systems Frontiers, Springer, vol. 0, pages 1-7.
    8. Neeraj Yadav & Ravi Shankar & Surya Prakash Singh, 2021. "Hierarchy of Critical Success Factors (CSF) for Lean Six Sigma (LSS) in Quality 4.0," International Journal of Global Business and Competitiveness, Springer, vol. 16(1), pages 1-14, June.
    9. Abdullah Mohammed Baabdullah, 2020. "Factors Influencing Adoption of Mobile Social Network Games (M-SNGs): The Role of Awareness," Information Systems Frontiers, Springer, vol. 22(2), pages 411-427, April.
    10. Gupta, Shivam & Kar, Arpan Kumar & Baabdullah, Abdullah & Al-Khowaiter, Wassan A.A., 2018. "Big data with cognitive computing: A review for the future," International Journal of Information Management, Elsevier, vol. 42(C), pages 78-89.
    11. Arenas, Alvaro E. & Goh, Jie Mein & Urueña, Alberto, 2019. "How does IT affect design centricity approaches: Evidence from Spain’s smart tourism ecosystem," International Journal of Information Management, Elsevier, vol. 45(C), pages 149-162.
    12. Joash Mageto, 2021. "Big Data Analytics in Sustainable Supply Chain Management: A Focus on Manufacturing Supply Chains," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    13. Rana, Nripendra P. & Barnard, Daniel J. & Baabdullah, Abdullah M.A. & Rees, Daniel & Roderick, Sian, 2019. "Exploring barriers of m-commerce adoption in SMEs in the UK: Developing a framework using ISM," International Journal of Information Management, Elsevier, vol. 44(C), pages 141-153.
    14. Olivia Benfeldt & John Stouby Persson & Sabine Madsen, 2020. "Data Governance as a Collective Action Problem," Information Systems Frontiers, Springer, vol. 22(2), pages 299-313, April.
    15. Olivia Benfeldt & John Stouby Persson & Sabine Madsen, 0. "Data Governance as a Collective Action Problem," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    16. Nripendra P. Rana & Sunil Luthra & Sachin Kumar Mangla & Rubina Islam & Sian Roderick & Yogesh K. Dwivedi, 2019. "Barriers to the Development of Smart Cities in Indian Context," Information Systems Frontiers, Springer, vol. 21(3), pages 503-525, June.
    17. Calvard, Thomas Stephen & Jeske, Debora, 2018. "Developing human resource data risk management in the age of big data," International Journal of Information Management, Elsevier, vol. 43(C), pages 159-164.
    18. Agung Wahyudi & George Kuk & Marijn Janssen, 2018. "A Process Pattern Model for Tackling and Improving Big Data Quality," Information Systems Frontiers, Springer, vol. 20(3), pages 457-469, June.
    19. Sushil,, 2018. "Incorporating polarity of relationships in ISM and TISM for theory building in information and organization management," International Journal of Information Management, Elsevier, vol. 43(C), pages 38-51.
    20. Paul Brous & Marijn Janssen, 2020. "Trusted Decision-Making: Data Governance for Creating Trust in Data Science Decision Outcomes," Administrative Sciences, MDPI, vol. 10(4), pages 1-19, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ininma:v:46:y:2019:i:c:p:124-141. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-information-management .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.