Big Data Analytics Assignment On Annotated Bibliographies

Question

Task: You are required to prepare for this Assessment Item by:

READING theSubject outline,
COMPLETING Topic 3, 4 and 5 on sections that discuss how to do anAnnoatated Bibliography and a Journal Synopsis paper.

WHAT TO DO: Tasks 1 and 2 below
TASK 1
Annotated Bibliography

Write an Annotated Bibliography for your Capstone Topicwith a collection of 12 articles following a set structure. The Annotated Bibliography is a critical examination of the most relevant and recent scholarly research on the topic area that is not just a summary of the articles you have read.
An Annotated Bibliographyis a detailed analysis of sources that can be used later in an expanded Literature Review.
Use the latest online search tools (CSU PRIMO, Google Scholar, Online databases) and efficient bibliographic organisers - CSU supports the use of EndNote. (available on iPad). EndNote is a bibliographic citation program, allowing references and footnotes to be translated into a variety of standard formats.
Ensure that the Annotated Bibliography submitted by you is your own work and has not been submitted elsewhere and comply with the University's requirements for academic integrity.
You can get help in Building and Writing an Annotated Bibliographyfrom several Topics in the ITC571 Interact2 site sidebar menu and other study advice and tips from:
1. Study Resources (PDF files to download): http://student.csu.edu.au/study/resources
2. APA style Referencing from http://student.csu.edu.au/study/referencing-at-csu
  Example below shows APA6 style with 2^ndand subsequent line indentation and use of DOI link to source if available:
3. The CSU Library website for LibGuides in Information Technology, Computing and Mathematics at http://libguides.csu.edu.au/cat.php?cid=66969
4. EndNoteBibliographic software and tutorials LibGuide at http://libguides.csu.edu.au/endnote
Review the emerging technology (use internet for journals, conference papers, magazines, news articles, online databases, eBooks) and submit a 12-article Annotated Bibliographyon your topic.
A good place to start a collection of articles in your annotated bibliography is via the PRIMO search tool located on the CSU Library websiteat http://www.csu.edu.au/division/library
Self-Evaluation Report on Originality (100-150 words)
1. Select an 1000-word sampleof annotations text only (exclude references) from and submit it for testing at Turnitin com
2. Save and append a copy of the originality report obtained.
3. Critically evaluate and interpret the originality report, from your context or point of view as your personal Self-Evaluation Report on Originality(100-150 words).
NOTE: Tasks 1 and 2 (below) can be appended into the one document and submitted via EASTS as PDF or other document format

As an example, the Capstone Topic PRIMO search on a research topic like "IoT security in smart cities" returned the following snapshot from a large list of very recent journals related to the Topic, by using the "articles" filter to cut out books, eBooks etc. Next when applying another filter "peer-reviewed" and a sort by "Date-newest", joined with a show only "Open access" and "Available Online", then the second screen reveals a 2019 journal paper not readily seen on the first broader search result page 1:

Answer

Introduction
According to opinion of Shafqat, Kishwer, Rasool, Qadir, Amjad & Ahmad, (2018) considered in the big data analytics assignment, Big Data Analytics refers to the process through which a large amount of data is collected, arranged and analysed. The analysis of big data helps in predicting certain outcomes and also gathering some very important information. The application of Big Data Analytics in healthcare systems can help in improving the services that are given to the patients. The spread of a disease can also be controlled, new ideas about the mechanisms of the disease can be developed, the healthcare and medical institutions quality can be improved, and methods of treatment can be enhanced through the application of Big Data Analytics.

Annotated Bibliography 1
Source: Journal Article

Belle, A., Thiagarajan, R., Soroushmehr, S. M., Navidi, F., Beard, D. A., & Najarian, K. (2015). Big data analytics in healthcare. BioMed research international, 2015.

Description: The authors recognise that the role of Big Data Analytics in the field of healthcare has become quite significant over the years. The research and practices in the healthcare sector are also dependent on the analysis of big data. The article used herein big data analytics assignment reflects that the advantage of the Big Data Analytics is that it provides different tools which facilitate the accumulation of data, management of the data, its analysis and assimilation. For the purpose of delivering care and exploration of a disease Big Data Analytics is being implemented.

Critique: The authors state that Big Data Analytics has low rate of adoption and development in terms of research as it faces some basic problems which are an inherent aspect of big data. The article highlights the areas of healthcare system like genomics; image and signal face some challenges pertaining to Big Data Analytics. However, the article does not give any proper solution to these problems.

Evaluation: The article explored in the big data analytics assignment has evaluated and discussed the results of the research conducted in the recent years, based on the usage of large volumes of multimodal healthcare data from disparate sources. This is likely to have a positive impact on care delivery within the healthcare system.

Annotated Bibliography 2
Source: Journal Article

Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65.

Description: The authors of the paper discussed in the big data analytics assignment suggest that the use of Big Data Analytics has the potential to enhance the quality of healthcare and medical services. It has also been stated in the article that application of Big Data Analytics will also help in lowering the cost of providing healthcare as well as minimise waste generation and prevent chances of error.

Critique: It is stated in this big data analytics assignment that the authors have highlighted one of the major drawbacks of the Big Data Analytics which is lack of availability of sufficient evidence for proving its benefits of application in healthcare because mostly all researches in this field have been qualitative. This is one reason for which the application of Big Data Analytics is limited. Though the article has pointed out the problem of scarce evidence yet it has not suggested a proper solution to this problem and has not even suggested how developing nations can widely implement Big Data Analytics.

Evaluation: The article provides an evaluation that focuses on the benefits of Big Data Analytics which are optimal utilisation of the clinical infrastructure, streamlining the operations and reducing operational costs.

Annotated Bibliography 3
Source: Journal Article

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.

Description: The authors emphasize on the fact that despite being very useful for healthcare systems the application of Big Data Analytics is still not grasped completely by the world. The technology based researches in the field of Big Data Analytics need to find their implications. The article utilized big data analytics assignment stresses on the study of design of architecture, development and functionalities of the components that are related to the Big Data Analytics.

Critique: The authors have reflected on the potentiality of Big Data Analytics to provide analytical strategies driven by big data. However, the article does not provide much information about the application issues with Big Data Analytics. The requirement of the management and capacity of the human resources to absorb, adopt and implement Big Data Analytics in healthcare has not been highlighted in the article.

Evaluation: The article evaluates the advantages of applying Big Data Analysis which are capability of analysis of unstructured data, ability to analytically understand the care patter, potential to support decision making, capability to predict and trace. The Big Data Analytics support the development of the healthcare system in the areas of operation, infrastructure, management, organisation, IT and strategic planning.

Annotated Bibliography 4
Source: Journal Article

Sharma, S., Chen, K., & Sheth, A. (2018). Toward practical privacy-preserving analytics for IoT and cloud-based healthcare systems. IEEE Internet Computing, 22(2), 42-51.

Description: The authors reflect in regards to the case scenario of big data analytics assignment that the healthcare systems today are dependent on the technology based cloud computing, internet of things (IoT) and big data analytics. The application of these technologies and analytics in the field of healthcare facilitates in collection of data, its management, storage and its analysis. The depth and scale of healthcare data analysis is unprecedented. The researchers, doctors, patients and providers of healthcare all rely on the results of health data analysis.

Critique: The authors highlights the major problem of application of cloud computing, Io and big data analytics in healthcare. The maintenance of privacy and safeguarding the data is the prime concern in case of technology based applications. The preservation of privacy in the system has to be further developed through research which is reflected in the article. However, the ways of overcoming the privacy issues have not been clearly stated within this big data analytics assignment.

Evaluation: The article evaluates that the application of big data analytics in healthcare system helps in better monitoring of the patients, develop ways of treatment which are personalised, diagnose the diseases at an early stage and suggest required medications on time. A personalised information system, kHealth for digital healthcare is developed for privacy assets’ identification, analysis and discussion before its practical application.

Annotated Bibliography 5
Source: Journal Article

Chen, M., Ma, Y., Li, Y., Wu, D., Zhang, Y., & Youn, C. H. (2017). Wearable 2.0: Enabling human-cloud integration in next generation healthcare systems. IEEE Communications Magazine, 55(1), 54-61.

Description: The authors emphasize on the prospects and potentials of applications like IoT, cloud computing and big data analytics which are powerful and comprehensive. The application of these technologies outlined in the big data analytics assignment in healthcare system will enhance the efficiency and reliability of services.

Critique: The authors state that the cloud technologies which are advanced like big cognitive computing and data analytics or terminal technologies like smart clothing make the healthcare system more intelligent in approach. However, the drawbacks of these advanced technology application like non-functioning of sensors or hacking of digital data have not been highlighted in the article.

Evaluation: The article provided in the big data analytics assignment evaluates the scope of advanced technology application like big data analytics and IoT in healthcare system in the coming generations. These technologies through machine intelligence facilitate the collection of physiological data of the patients, understanding their emotional status and drawing the inference from their health data analysis.

Annotated Bibliography 6
Source: Journal Article

Barry, M. J., & Edgman-Levitan, S. (2012). Shared decision making—The pinnacle patient-centered care.

Description: The authors focus on the need of care which is patient centered so that their requirements, values and preferences are considered during the clinical treatment. The big data analytics help in collecting all the relevant data to maintain this patient centric healthcare system. The doctors and patients can together contribute to the process of data accumulation and depend on its analysis results.

Critique: The authors reflect on the significance of big data analytics when medical decisions reach a crossroad. However, the optimal decision making is not always a shared decision of the participants of the clinical treatment process. The article presented within this big data analytics assignment does not address how the reality of decision making is derived from the rhetoric. Regularly engaging the patients in the decision making is still lacking as they do not get full access to the analytical outcomes.

Evaluation: The article examined herein big data analytics assignment has evaluated that the healthcare system can become more responsive and personalised in its approach if the patient’s decision is taken into account while providing the care. The clinicians will be able to cater to the needs of patients in a better way if they share the analytical results with the patients and involve them in the decision making regarding the treatment.

Annotated Bibliography 7
Source: Journal Article

Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data analytics-enabled transformation model: Application to health care. Information & Management, 55(1), 64-79.

Description: The authors focus on the transformation model which is enabled by Big Data Analytics. Through this model the relationship between the capabilities of big data analytics, dimensions of its benefits, transformation practices of IT and business values are revealed. This transformation model has found its application in healthcare system and generated great benefits.

Critique: The authors have emphasized on the capabilities of Big Data Analytics, its strategic benefits and potentials of application in healthcare system. The aspects which are neglected in the article are the prospect of adaptability of Big Data Analytics in healthcare, the hindrances in application and solutions to the problems.

Evaluation: The article evaluates the application of the transformation model in the three paths which is significant to the value chains of supply. These value chains are an integral part of the healthcare system and the application of Big Data Analytics in these areas will provide the managers with a pragmatic insight.

Annotated Bibliography 8
Source: Journal Article

Manogaran, G., Thota, C., Lopez, D., Vijayakumar, V., Abbas, K. M., & Sundarsekar, R. (2017). Big data knowledge system in healthcare. In Internet of things and big data technologies for next generation healthcare (pp. 133-157). Springer, Cham.

Description: The authors focus on the need of big data analytics in healthcare as a huge amount of health data has to be accumulated, recorded and analysed. The electronically and digitally available data for patients’ care, healthcare compliance, record maintenance, regulations, etc. helps the clinical process to progress fast.

Critique: The authors reflect on the utilisation and productive outcome of application of medical imaging data, genetic data, maintaining Electronic Health Record (EHR) and keeping unstructured clinical notes. But the lack of synchronisation of the big data during the process of analysis and the reasons behind it is not addressed on the article.

Evaluation: The article evaluates the growth in clinical analytics with the help of big data analytics. This information provided in the big data analytics assignment has facilitated analysis of large data and also provided practical medical insights regarding its implications. The article has highlighted that big data analytics support proper monitoring of data, surveillance of the illness, decision making and healthcare management.

Annotated Bibliography 9
Source: Journal Article

Manogaran, G., Varatharajan, R., Lopez, D., Kumar, P. M., Sundarasekar, R., & Thota, C. (2018). A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generation Computer Systems, 82, 375-387.

Description: The authors reflects on the fact that wearable medical devices leads to continuous generation of vast data through sensor that is known as big data mixed with unstructured as well as structured data.

Critique: The article used in this part of big data analytics assignment illustrates about the issue that takes place while analysing the big data to gather valuable information. It also reflects on the way to overcome the issue through new architecture that will impalement Internet of Things to initiate scalable sensor data for healthcare applications. This is shown through multiple models supported by strong referencing.

Evaluation: The article provides an evaluation about the intended architecture that is required to observe patients health. The performance evaluation of the planned health monitoring system has been carried out with the help of Sensitivity.

Annotated Bibliography 10
Source: Journal Article

Chen, M., Li, W., Hao, Y., Qian, Y., & Humar, I. (2018). Edge cognitive computing based smart healthcare system. Future Generation Computer Systems, 86, 403-411.

Description: In this big data analytics assignment, the article provides an overview on the way healthcare system has witnessed an interest surge due to rapid development of medical as well as computer technologies.

Critique: The issue outlined herein big data analytics assignment related to falling short to regard emergency circumstances of patients in healthcare systems has been critically evaluated in the article. As a result, the article illustrates the usage of Edge-Cognitive-Computing-based smart healthcare systems that has been explained in accordance to resource cognitive engine as well as data cognitive engine.

Evaluation: The importance to compute risk level of disease has been evaluated through appropriate measures such as physiological data as well as other disease-related information. This in turn provides great assistance to healthcare professionals.

Annotated Bibliography 11
Source: Journal Article

Keen, J., Calinescu, R., Paige, R., & Rooksby, J. (2013). Big data+ politics= open data: The case of health care data in England. Big data analytics assignment Policy & Internet, 5(2), 228-243.

Description: The article provides an overview about Big Data that is carried out globally in healthcare systems. Health care emerges to provide the perfect amalgamation of circumstances, with a requirement to perk up output on the one hand and the ease of use of data that would help to recognize opportunities for productivity developments on the other.

Critique: The importance of NHS data as well as information technology policies that aids to carry out bureaucratic arrangements has been explained with the help of explicit referencing.

Evaluation: A critique related to open data policies as well as their challenges has been critically evaluated in the present big data analytics assignment that deals with a set of ideas.

Annotated Bibliography 12
Source: Journal Article

Salas-Vega, S., Haimann, A., & Mossialos, E. (2015). Big data and health care: challenges and opportunities for coordinated policy development in the EU. Health Systems & Reform, 1(4), 285-300.

Description: The article aims to outline the anticipated results that go hand-in-hand with the healthcare sector. The initiative that promotes using big data in healthcare sector has been examined in the article.

Critique: The article avail in this section of big data analytics assignment critically examines the challenges that take place during successful integration of big data in healthcare. A comprehensive approach that comprises of electronic data as well as specialist website searching has been explained in detail through in-depth referencing.

Evaluation: The article explored herein big data analytics assignment evaluates a detailed search strategy that reflects on the fact that additional development in the big data policy is required. It has been evaluated that the big data has the probability to enhance healthcare systems.

Conclusion
It could be concluded from the above analysis on big data analytics assignment that the integration of big data analytics in the form of sensor devices helps to provide security services to healthcare systems. It also helps to initiate continuous monitoring in healthcare systems thus improving the sector. Data security has turned out to be an imperative aspect in healthcare system that has increased the requirement to introduce big data analytics.

Self-reflection
It could be reflected on this section of big data analytics assignment that big data analytics provides advantage to healthcare systems. It could be inferred that a sequential transformation takes place in healthcare systems due to IT-enabled practices. The topic is related to present big data analytics that is known to improve organizational practices thus influencing competitive advantages. The articles reflect on the fact that implementing big data analytics is based completely on case materials that delineate its impact on healthcare system. It could be inferred that transformation in healthcare in the course of big data analytics has been at their initial stages of evolutionary revolution. It could be reflected that in order to store big data it is imperative to involve database clusters as well as additional resources. In other words, big data has been used in healthcare systems to increase sizes of clinical record that are accessible online.

Journal Synopsis
The aim of the project on big data analytics assignment has been to show the way big data analytics has been able to transform the healthcare systems. This in turn reveals that there exists a causal relationship among capabilities related to big data analytics. The methods that are used involve an epistemological approach that is mostly grounded on interpretivism paradigm. The methods mostly involved qualitative inputs from major policy stakeholders. The results illustrates that the challenges that takes place in healthcare systems are eradicated through successful incorporation of big data analytics. It could be discussed that the intended healthcare systems has helped to examine the performance that takes place within healthcare community. It could be concluded that the cognition of data helps to solve all healthcare related issues.

References
Barry, M.J. and Edgman-Levitan, S., 2012. Shared decision making—The pinnacle patient-centered care.

Belle, A., Thiagarajan, R., Soroushmehr, S. M., Navidi, F., Beard, D. A., & Najarian, K. (2015). Big data analytics in healthcare. Big data analytics assignment BioMed research international, 2015.

Chen, M., Li, W., Hao, Y., Qian, Y., & Humar, I. (2018). Edge cognitive computing based smart healthcare system. Future Generation Computer Systems, 86, 403-411.

Chen, M., Ma, Y., Li, Y., Wu, D., Zhang, Y., & Youn, C. H. (2017). Wearable 2.0: Enabling human-cloud integration in next generation healthcare systems. IEEE Communications Magazine, 55(1), 54-61.

Keen, J., Calinescu, R., Paige, R., & Rooksby, J. (2013). Big data+ politics= open data: The case of health care data in England. Policy & Internet, 5(2), 228-243.

Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65.

Salas-Vega, S., Haimann, A., & Mossialos, E. (2015). Big data and health care: challenges and opportunities for coordinated policy development in the EU. Health Systems & Reform, 1(4), 285-300.

Shafqat, S., Kishwer, S., Rasool, R. U., Qadir, J., Amjad, T., & Ahmad, H. F. (2018). Big data analytics enhanced healthcare systems: a review. Big data analytics assignment The Journal of Supercomputing, 1-46.

Sharma, S., Chen, K., & Sheth, A. (2018). Toward practical privacy-preserving analytics for IoT and cloud-based healthcare systems. IEEE Internet Computing, 22(2), 42-51.

Wang, Y., Kung, L., Wang, W. Y. C., & Cegielski, C. G. (2018). An integrated big data analytics-enabled transformation model: Application to health care. Information & Management, 55(1), 64-79.

Tags: anotated bibliography health care big data medical computer science

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