Context and Concerns of Contemporary Research in Computing: A Brief Overview for New Researchers

Posted on December 15, 2017


Author:   Sanjay Goel


Many students and researchers often have a very narrow view of computer science. This post gives a brief and broad overview of contemporary trends in computing research. As can be seen, the spectrum of research questions and objectives in and around computing is really very wide and there is enough opportunity to accomodate a huge diversity of scholarly interests.  However, in the absence of such an awareness, often the new scholars start their research in the areas that may not be in alignment with their core strengths or real interests.  This sometimes results in under-utilisation of their strengths and potential and they may end up producing mediocre quality research in such areas.   It is hoped that this brief post will help the new researchers and scholars  to more carefully identify their research area so that they can really enjoy and also achieve excellence in their research.

In the last several decades, computational interventions have significantly impacted the physical, biological, psychological, and social worlds. Computing has either transformed or has demonstrated the possibility to transform the workflows, workspaces, and the fundamental nature of the work nearly in all domains of production and services. It has also reshaped the personal and social spaces as well as the leisure. It has done so by redesigning the activities related to monitoring & control, search & exploration, problem solving & research, and artistic rendering & creations. It has not only made possible to automate and improve the existing methods, but has also helped in developing many novel ways of observation, management, analysis, experimentation, modelling,  evaluation, synthesis, rendering, communication, and even collaboration. These novel interventions and transformations have been possible because of computing systems’ ever-increasing ability to automate the processes to collect, store, integrate, analyse, transfer, and transform very large volumes of data – quantitative or qualitative, single or multi-dimensional, corpus or stream, invariable or dynamic, static or kinetic, centralised or distributed, structured or unstructured, facts or rules, measured or simulated, multimedia or multimodal, exact or fuzzy, confined or pervasive.  Depending upon their interest, the new research scholars can formulate their research objectives regarding automation of such processes with respect to different types of data sources and forms to either redesign some chosen activities and/or spaces or even create new ones.

The computing researchers are primarily motivated by the questions about the abstract expressions of structures and processes and also the automated rendering and actualisations of those abstractions. They build and experiment with domain-specific systems and carry out specific generalizations over a chosen class of systems. Their research questions relate to design, development, or performance evaluation of automation systems, paradigms, and methods for data collection, storage, processing, and communication as well as knowledge discovery and learning. They deal with questions about complexities, uncertainties, complications, and risks associated with these systems and methods. They evaluate their results and findings with respect to the constraints and success criteria related to functionality, performance, cost, schedule, technology, scalability, usability, acceptability, security, regulations, safety, health, energy, privacy, environment, and elegance among other factors.  After formulating their  research objectives, the new computing researchers  can formulate an  array of appropriate research questions and sub-questions around evolving constraints and success criteria with respect to specific work domains’ requirements.

Conventionally, the computing research was divided into five main overlapping subfields – computer science, computer engineering, information science, information technology, and software engineering. Since the beginning of the computer science, the dream and the ever-expanding possibilities of the artificial intelligence, has been pushing the boundaries of the research agenda in all these subfields. Pervasive & cloud computing and computational & data sciences are its newer research frontiers offering novel prospects for complex problem solving, system designing, understanding human behaviour, and also investigating new questions that were not dared before because of the scale challenges. Computing researchers are diligently working on these frontiers to leverage and create newer opportunities. However,  engagement  in these newer knowledge areas also results in mediocre work when the research  objectives and research questions are not formulated well.   In order to work on the new research frontiers, the scholars working in all such newer knowledge areas also should first try to properly formulate their objectives and research questions.

For improving the computing profession related practices, researchers investigate and develop new methods and tools for systems and software engineering on one hand and computing education and training on the other. Their research concerns also include the possibilities and challenges of using Information and Communication Technology (ICT) for human and societal development as well as issues related to equity, accessibility, environment, and sustainability. ICT playing a progressively central role even in the personal and social lives, the contemporary computing research also re-examines and re-interprets some fundamental human issues related to cognition, affect, dignity, justice, ethics, democracy, and happiness.   Many Computing researchers engaged in  interdisciplinary  work also include some of these traditional as well as emerging concerns.  Increasingly many of them try to align their research concerns with the UN defined Sustainable Development Goals (SDGs) and targets related to the environment, health care, education, heritage, rural development, and other such issues.  Computing scholars also have a great opportunity to explore such opportunities to integrate their  expertise, multidimensional interests  and larger concerns to develop innovative computing solutions for addressing some such issues.

Performance assessment is a key step in most computing related research activities. Performance assessment methods use analytical modelling, simulation, and empirical measurement techniques. Computing systems’ performance claims often get weakened because of oversights, misconceptions, undefined/biased goals, wrong assumptions, incorrect metrics, unrepresentative workloads, overlooked parameters, ignored factors, inappropriate experiment design, erroneous analysis, wrong evaluation techniques, or unsystematic approach. The scholars are advised to be more careful about such pitfalls from the beginning itself in order to avoid creating mediocre work.   Experienced researchers also work to develop the performance assessment methods, metrics, datasets, benchmarks, tools, workbenches, and modelling techniques across different computing areas.  New scholars can also contribute to such efforts.


Other related articles on this blog:

  1. Research Method for Engineering Research Students – Part I: A Checklist for Literature Review-
  2. Research Method for Engineering Research Students – Part II: A Checklist for Reflective Self-assessment of the Research Work-
  3. Research Method for Engineering Research Students – III: Some Insightful Quotes about Philosophy, Science, Inquiry, and Research-


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