Information Science vs. Computer Science: What's the Difference?

Though they share similarities, information science and computer science are separate and distinct fields taking over the job market and driving technological innovation and advancement. While both play important roles in shaping the digital world, their approaches, methodologies, and areas of focus vary significantly.

If you’re considering furthering your education in one of these two areas, you must fully understand their similarities and differences. Doing so will give you a better picture of which path fits your academic interests, career goals, and professional journey.

Understanding the Computer and Information Sciences

What is information science?

• Information science is the study of information and its interaction with society, organizations, and individuals. It emphasizes the management and organization of information and the human aspects of information processing and technology. This field may incorporate principles of information technology and library science.

What is computer science?

• Computer science is the study of computational processes and systems, including software development, algorithm design, programming languages, and theoretical foundations of computing. This field is deeply rooted in problem-solving, leveraging mathematical principles and logical reasoning to develop innovative software and systems.

Approaches and Methodologies to Computer Science vs Information Science 

Understanding how information science and computer science approach problem-solving highlights the key differences between these fields. While both leverage technology and computational techniques, their methodologies and focus areas set them apart.

Information Science

Information science is an interdisciplinary field that applies a range of methodologies to manage and extract insights from data. It ensures information is accessible, accurate, and relevant by:

• Using algorithms in data management and retrieval to structure and organize information effectively
• Incorporating knowledge representation techniques and classification methods, such as taxonomies, ontologies, and metadata to categorize information for better navigation and understanding

Computer Science

In contrast, computer science focuses on solving computational problems through software development and algorithmic solutions. It applies mathematical principles and structured problem-solving to:

• optimize processes using algorithms and models to improve efficiency in software applications
• develop software by translating theoretical algorithms into functional solutions, incorporating steps such as designing, coding, testing, and debugging

Both fields greatly impact the tech industry by addressing challenges related to data, software, and system design.

Applications in the Tech Industry for Information Science vs Computer Science 

The applications of information science and computer science in the tech industry vary, with each offering unique contributions to different aspects of development and innovation.

Information Science

Information science principles drive efficiency in multiple areas of the tech industry, especially where data organization and user interaction are key. Applications include fields such as:

Information science professionals are also involved in developing advanced tools that streamline information retrieval and decision-making. This includes creating search engines, digital libraries, and data analytics platforms, all of which are essential for improving how we access and use information in today’s digital world.

Computer Science

Computer science principles are the cornerstone of technological advancements across various sectors and are used in software development processes to create programs that power modern technological ecosystems. Computer science is integral to fields like:

Computer science also influences the creation of new programming models and computing frameworks, which power modern digital infrastructure. These innovations help build the systems and technologies that power everything from cloud computing to internet security.

Given how both fields shape the tech industry, applying that knowledge of their applications to career opportunities can help you determine which path aligns with your skills and goals.

Computer and Information Science Jobs and Skill Sets 

The skill sets and career opportunities within the computer and information science fields are also distinct, despite how often they intersect in the tech industry. Let’s explore how careers in these fields compare.

Information Science Jobs 

Professionals in information science need expertise in data management, information retrieval, and knowledge organization. Career options can extend beyond data science and information architecture, including roles like:

• Tech consultant: advising businesses on information systems and data strategies
• UX designer: creating user-centered designs for digital products and interfaces
• Cybersecurity analyst: protecting data and networks from cyber threats
• Project manager: overseeing the development of information systems and technology projects
• Data analyst: interpreting complex data to drive business decisions

Computer Science Jobs

Computer science careers demand strong programming, algorithm design, and computational thinking skills. Professional opportunities can include roles like:

• Software engineer or systems developer: building applications and platforms
• AI and machine learning specialist: advancing intelligent computing solutions
• Network administrator or cybersecurity analyst: ensuring the integrity and security of digital systems

Become an Information and Computer Science Professional at Cornell Bowers CIS

Although information science and computer science are distinct fields, they often work together to drive technological innovation. Information science focuses on organizing and managing data to ensure accessibility and relevance, emphasizing user-experience design. On the other hand, computer science is concerned with developing algorithms, software, and systems, prioritizing efficiency and scalability. However, as technology evolves, the difference between the two fields becomes increasingly blurred, fostering collaboration between data management and computational problem-solving.

At Cornell Bowers CIS, the MPS in Information Science program stands at the intersection of these fields, offering a dynamic, interdisciplinary education beyond traditional data management. This program isn’t just about working with data—it’s about studying computing and information in context, addressing human values, cultural implications, and ethical considerations in technology.

Why choose Cornell Bowers CIS’s MPS in Information Science?

• Interdisciplinary focus: Explore computing, data, and information systems through the lens of ethics, law, and policy.
• Hands-on experience: Gain real-world skills through the MPS project, applying classroom knowledge to industry-level challenges.
• Flexible career paths: Prepare for roles in tech consulting, UX design, software development, cybersecurity, and beyond.

Learn more about course offerings, career pathways, and how you can tailor the MPS program to elevate your career by exploring our free resource—Crafting Your Information Science Master’s Program.