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More Metadata Please! Advanced Media Asset Management Driving Data Journalism
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More Metadata Please! Advanced Media Asset Management Driving Data Journalism

Moments Lab Content Team
July 6, 2021

The more (metadata) you know!

Metadata…even if you don’t know what it is, you probably know it’s important 💡

Commonly described as ‘data about data’, metadata refers to a high-level summary of existing data that can help users understand information in a new way. It takes into account an item’s description, title, and keywords (among other elements), which can be manually or automatically derived.

Although it can be used for classification and security objectives, one of its primary uses is enabling enhanced ‘searchability’, finding specific data instances. When combined with a filter system, metadata is an invaluable search & retrieval tool, allowing users to target extremely particular queries i.e. date, time, person, objects, etc.

Among your media assets, metadata can be used to optimize content for advanced search and retrieval.

Data Driven Journalism: New Approach Revolutionizing Storytelling

According to datajournalism.com,

“Data journalism is an umbrella term that, to my mind, encompasses an ever-growing set of tools, techniques and approaches to storytelling. It can include everything from traditional computer-assisted reporting (using data as a ‘source’) to the most cutting edge data visualization and news applications. The unifying goal is a journalistic one: providing information and analysis to help inform us all about important issues of the day.”

Journalists are creating, documenting and transferring metadata on a daily basis. Although we tend to think of data exclusively as numbers, it also relates to qualitative information as well. As they relate to datasets- photos, videos and audio all correspond to zeros and ones.

One of the main objectives of Data Journalism is to tell compelling stories via structured data. Essentially using data to create deeper insights. This concept goes back to metadata- understanding information in a new way based on structured data.

But it’s not just that.

According to the American Press Institute, this new approach is helping journalists:

– Take a more authoritative stance on backing up and verifying story facts and claims

– Take on the ‘big stories’ that cover copious amounts of content

– Discover deeper meaning in complicated or emerging or past news stories

– Find new stories

– Create more efficient editorial workflows

News is data! Even the most complicated stories can be reduced down to binary numbers.

Aggregating and indexing thousands of hours of news content to see the ‘big picture’ is not always easy or even possible from a human perspective. Journalists work with an array of media assets, and at the end of the day, the common denominator is data. By combining small and seemingly meaningless data points, sometimes important information is revealed by connecting the dots.

So how exactly are journalists getting from point A to point B?

Multimodal AI Cross-Analysis: Advanced Searching and Visualization of News Content

Well the real question is how are they cross-analyzing point A, B and perhaps C to not just connect the dots, but instantaneously and simultaneously find, visualize and analyze a more complex angle or extremely specific sequence?

It’s not just about metadata, it’s also about how you use it.

Evolving technology plays a pivotal role in leveraging this data, and adapting to unique dataset structures. For journalists, smart media asset management is a crucial element for advanced storytelling. By adopting a cloud-based MAM that uses Multimodal AI to identify and even generate more metadata (sources, annotations, transcriptions, people, labels, organizations, dates, custom programs, etc.) paired with automatic indexing for advanced searchability, data driven journalism suddenly comes to life.

Using a semantic search engine that can cross analyze multiple auto-indexed elements, i.e. people, objects, speech to text, logos, context etc., journalists are able to piece together stories in seconds, possessing an in-depth precision of recently uploaded or incoming live media. In this way, exact and meaningful sequences (i.e. @Antoine Griezmann, #FFF, #EDF) can be found and published in record time.

Journalists are leveraging existing and auto-created metadata to tell accurate stories, faster.

The Future of Data Driven Journalism

As renowned french journalist Hervé Brusini puts it:

Statistics is the mother of journalistic purpose.

Gone are the days of journalists stopping by the local pub to collect information and perspective. It hasn’t been overnight, but as a society we’ve shifted into the 21st century. Over the past several years we’ve adapted to a data driven world, and now more than ever, that’s what readers want. Every day we expect stats on unemployment, taxes, polls, death, emissions… the list goes on.

So it only makes sense to use data to find this data!

It’s important to mention that data journalism is not replacing conventional journalism. On the contrary, it is a tool to help journalists do what they do best-investigative research, fact checking and storytelling.

With digital transformation driving advancements across the broadcast and media industry, numerous operational, editorial and financial benefits are expected.

One of the main objectives of data-driven journalism is also to eliminate information asymmetry in order to aggregate news stories faster. According to datajouonalism.com, information asymmetry is “not the lack of information, but the inability to take in and process it with the speed and volume that it comes to us”.

In a way, this limitation is quite paradoxical. Journalists are dealing with so much information that it’s sometimes difficult to extract the data that actually matters 🤷

By adopting a cloud-native platform and creating workflows that favor remote collaboration, easy access to users’ news content and next-level search & retrieval powered by Multimodal AI, journalists can work faster while identifying exact moments and drawing deeper and more meaningful inferences from hours of cross-analyzed content (photos, video, audio).

The equation is simple: quicker publication times = greater profitability.

About Moments Lab

Moments Lab (ex Newsbridge) is a cloud media hub platform for live & archived content.

Powered by Multimodal Indexing AI and a data driven indexing approach, Moments Lab provides unprecedented access to content by automatically detecting faces, objects, logos, written texts, audio transcripts and semantic context.

Whether it be for managing and accessing live recordings, clipping highlights, future friendly archiving, content retrieval or content showcasing and monetization - the solution allows for smart & efficient media asset management.

Today our platform is used by worldwide TV Channels, Press Agencies, Sports Rights Holders, Production Houses, Journalists, Editors and Archivists to boost their production workflow and media ROI.

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