"Are data and information different?"
Yuki asked Aoi while searching for materials in the library.
"Good question. Many people confuse them."
Aoi closed the book and began explaining.
"Data is raw facts. Arrays of numbers or symbols. But information is data with meaning."
"Having meaning?"
"For example, the data '42.' That alone isn't information. But 'Temperature is 42 degrees' has context and meaning."
Yuki began to understand. "Context is important."
"Yes. By giving context to data, it becomes information. This is the contact point between information theory and the real world."
At that moment, Professor S. entered the library.
"Having a good discussion."
"Professor, we were talking about the difference between data and information."
Professor S. sat down. "There's a metaphor of a sea of data. Modern society overflows with vast data, but most is unprocessed."
"Unprocessed?"
"Raw data is like petroleum. Value emerges only after refining."
Aoi supplemented. "Data mining and machine learning are technologies to extract information from data."
Yuki wrote in the notebook. "Data → Processing → Information → Understanding → Knowledge"
"Good diagram. Furthermore, it evolves from knowledge to wisdom," Professor S. acknowledged.
"But," Yuki thought. "In information theory, information content can be quantified, right? Doesn't distinguish between data and information?"
Aoi answered. "Sharp point. Strictly speaking, information theory handles 'information content.' This is a statistical concept, independent of meaning."
"Independent of meaning?"
"For example, random number sequences have high information content. But meaningless to humans. Conversely, poetry has low information content but deep meaning."
Professor S. continued. "This is both the limitation and strength of Shannon information theory. By excluding meaning, universal mathematics could be constructed."
Yuki looked troubled. "Then how to measure meaningful information?"
"That's the challenge of semantic information theory. Still a developing field."
Aoi gave a practical example. "Email subject 'Meeting' alone versus 'Tomorrow 3PM, Conference Room 3, budget meeting' has more information content. But what if the receiver already knew?"
"Information content decreases," Yuki answered.
"Right. Information value depends on receiver's knowledge state. This is the concept of subjective information."
Professor S. said quietly. "To not drown in the sea of data, the ability to find meaning is necessary. That's humanity's role."
Yuki looked outside the window. Beyond the library, the city spread out.
"The whole city is a sea of data. People's actions, temperature, time. All data."
"But when you find meaning in it, data becomes information," Aoi said.
"Information theory is a tool. How we use it is up to us."
Professor S. nodded. "Exactly. Technology is neutral, but application carries responsibility."
Yuki closed the book. Today again, a new perspective gained.
"Two people floating in a sea of data," Yuki murmured.
"Three people," Professor S. smiled.
"And connected with countless others. Through information," Aoi added.
The library was quiet, but invisible information flew about. Data is everywhere. But finding meaning is human work.
Yuki stood up. "I'll learn more. From data to information, from information to knowledge."
"That attitude is the most valuable information," Professor S. said quietly.
The sea of data is vast. But if you learn to swim, you can find treasure.