Metadata: What can you learn from it?

As technology keeps enhancing our lives, we continue to allow apps and programs to weave into our everyday activities. Fitness apps track our run times, calories burned, heart rate, and give us feedback on our progress. Facebook shows us ads of the products we talked about last week and suggests possible friends to add when we were just introduced yesterday. Our GPS apps give us notifications on the traffic for our usual Monday commute to the gym, our Tuesday grocery store trip, and even faster routes home.

But have you ever wondered how these apps do this? It all starts by learning what data is and how metadata can teach you so much about yourself. This article will discuss how data and metadata is being used, how it plays a part in your life, and the potential for metadata to evolve our relationship with the world.

What is a Data?

Data is just raw numbers, characters, or symbols without much meaning or use. When hearing the word “Data”, most people visualize bar graphs, pie charts, and spreadsheets; which is true, but data stems from a much older source. Long before computers were ever invented to process data into these graphics, us humans have been processing data ourselves with our brain. Data is as old as sensation itself, and the ability to process data has played a huge role in the evolution of the species that are still alive today.

On its own, data is useless and meaningless; but if organized and structured, data can become information that describes facts or details. Our eyes, nose, ears, skin, and tongue constantly receive data. Loud beeping, heat, softness, vibrating, brightness, sweetness are all forms of data. This type of data is received with our senses and being input in our brains. In the same sense data in computers are being input to the central processing unit or CPU. Whatever that is input to the CPU like the bits, bytes, letters, and numbers, is raw data and needs a structure or rule to be turned into information.

Picture a pie chart or bar graph without any labels. That is data processed into some form of information. Is this information useful? Probably not. Without a point of reference, it is nearly impossible to measure data. This is because there are no rules or structure, and without rules or structure, there are no measurements.

What is Metadata?

The definition of metadata is “data that provides information about other data”. In order to make rules and structure of data to become useful information, metadata is used. Metadata can be hidden from viewers or displayed on purpose. Metadata describes the main data and assists in consuming, forming, or managing the content. There are three main kinds of metadata which includes descriptive, structural, and administrative.

Descriptive, Structural, & Administrative Metadata

Descriptive metadata is the broadest, and provides further details for users to interact with the main data. Examples of descriptive metadata for online documents are the file size, creator, word count, file type, date created, and more. Structural metadata connects the relationship of data and its presentation to the user. Examples of structural metadata are page numbers, location, or chapters. Lastly, administrative metadata aids in the management of data and is usually hidden from outsiders. Examples of administrative metadata are owner, copyright, or license information. Metadata can also refer to when the data was collected, the location it occurred, where the data was sent, and just about anything related to the data itself.

Referred to as data dictionaries, metadata shows relevant information about data. In a spreadsheet, a column full of numbers would have no distinctive meaning. But if you add a descriptive metadata “Dollars each month” as the header of the column, you can begin to form an idea of what the data means. Continuing with structural metadata “Account Balance”, the data is organized into separate statements for each month. Finally, adding the administrative metadata “Owner: John”, this denies access to the data of anyone that is not the owner. Adding descriptive, structural, and administrative metadata transformed a group of random numbers into a bank account database.

Earlier examples of data were mentioned as loud beeping, heat, softness, vibration, brightness, sweetness. Using metadata to describe sensations we experience, we know the beeping is a sound that we are hearing and it’s coming from our alarm clock. In fact, metadata is so deep in our existence that we forget that words are actually random useless combinations of data. Metadata refers these words as things that people read, and finally we process the words into information.

Have you have ever heard a strange noise coming from behind you and freaking you out? You’ve never heard this noise before and the unknown scared you. This is an example of data that was received but did not have any metadata to describe its relation, and therefore your brain did not know how toprocess it and freaked out.

The difference between animals and humans is how data is processed

Both animals and humans process data with their senses and brain. Animals use metadata to group sounds of branches snapping as predators behind them, group colors on food as poisonous, or group scents they smell as potential mates. Those examples are using metadata as a means of survival. The color red on its own has less use versus the color red with metadata as apple and information as ripe. After many, many years of using metadata to form processes of information, these processes were ingrained in various species as instinct.

Humans use metadata in an advanced form to process data into useful information beyond survival needs. From the discovery of fire itself all the way to the creation of computers, humans have been using metadata to form relation between data to thrive. Eventually reaching the programs and apps used today, humans use our data inputs in tools to make our lives easier.

So what can you learn from metadata?

Currently metadata can teach a lot about a person and their habits. Since everything a person does online leaves a trace, metadata can connect everything and show a relational effect of different actions. Similar to reverse engineering the butterfly effect, the power of metadata can deepen our understanding of people’s behaviors. We can learn how the amount of social media we consume affects our happiness levels, we can graph the strength of our relationships throughout time using texts, and we can assess how tiring our day at work was depending on whether we had the energy to go to the gym afterwards.

In a TedX talk, “The Power of Metadata: Deepak Jagdish and Daniel Smilkov”, Deepak shown a bar chart that represented the amount of emails he sent and received throughout a few years. A period of a few months showed a severe decrease in the amount of emails compared to the rest of the time. When his colleague saw this, he asked if Deepak he went through a traumatic period of his life during that time. Without knowing any personal information, his colleague was able to guess changes in Deepak’s life through the metadata of email quantities.

Overall, using metadata can be a huge invasion of privacy and have a negative reputation; but it can also be used for good. Metadata has the potential to predict if someone has a life-threatening disease, if someone is about to harm another, or maybe even harm themselves. The future of data has potential to save many lives, or harm many lives. The determining factor is where we as a species will focus our efforts. In conclusion, data itself is useless, only when processed into information can it be used by humans for a purpose.

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