Learn how companies can tap into the power of the data coming their way by integrating the huge data flows with their proprietary data.
Making Sense of Text and Data
Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model
Interlink your organization’s data and content by using knowledge graph powered natural language processing with our Content Management solutions.
Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.
Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more
Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more
Connect and model industry systems and processes for deeper data-driven insights in:
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.
Unlock the potential for new intelligent public services and applications for Government, Defence Intelligence, etc.
Connect and improve the insights from your customer, product, delivery, and location data. Gain a deeper understanding of the relationships between products and your consumers’ intent.
Link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.
Organize your information and documents into enterprise knowledge graphs and make your data management and analytics work in synergy.
Integrate and evaluate any text analysis service on the market against your own ground truth data in a user friendly way.
Turn strings to things with Ontotext’s free application for automating the conversion of messy string data into a knowledge graph.
From the late 1950s, ever since the computer began to move slowly but steadily from the laboratory to the market, media have hopped on the wave of public concern, rising from questions such as:
Will Giant Brains Rule the World?
Can a mechanical brain replace you?
Computer Top Foe of People?
These are real questions from newspapers and TV programs (note to the curious: The Machine That Changed The World, Youtube series).
Today, a similar wave of conflicting emotions arises when it comes to the role of intelligent agents in our public and private lives. Many repeatedly express their concern about how building smart systems (“brains”), which can outsmart us in certain ways, will affect our lives.
The question is to what extent this linking of databases and the automatic analysis of information is important. And can we speak of a giant automatic brain, larger than any human intelligence taken separately?
Admittedly, the brain-computer parallel is lucrative and buzz-friendly, but it is also reductionist. While there are similarities (take semantic networks as the most prominent example of a similarity between the brain and computer structures), bringing computation to decision-making and data processing is not exactly like building a brain.
It is rather like building an extension to the human brain. Like designing complex data processing systems that are able to intelligently communicate, process and store information on our behalf. Think of such systems as a kind of extension, the kind Marshal McCluhan talks about in Understanding Media: The Extensions of Man:
all technologies are extensions of our physical and nervous systems to increase power and speed.
Cit. Understanding Media: The Extensions of Man
Remember Captain Mifune from the movie The Matrix? More specifically, the scene where he is in his APU (the hydraulic Armored Personnel Unit, designed for combat), leading the primary line of defense for Zion?
Now extrapolate that image onto the digital plane and picture a data worker, or, let’s say, a content manager who is defending their enterprise from the upcoming terabytes of data that come right at their face. To confront those and use them, more than smarts are required. The way this challenge is met also requires smart data: cognitive acumen armored with machine intelligence for interacting with the outer data world efficiently and effectively.
Smart data is how we build such an “extension” of our own ways of knowing as to intelligently organize and communicate massive amounts of data so that these data do not overwhelm but empower us.
For we need to brace ourselves (and our cognitive powers) for the computational-knowledge economy. In it, smart decisions are unthinkable without smart data processing. The real question is not whether a mechanical brain will replace us but how we can enhance our brain powers with the computing and analytical powers of machines.
We need to stand on the power of automation […] and learn to go further. We need not make us humans compete with computers as we will fail.
Cit. Conrad Wolfram, at Webit
We can design intelligent processes or do analysis with the cognitive aid of algorithms that can help us immensely when managing our data. Take semantic annotation, for example. It is a smart means for us to enhance our text analysis process.
Semantic annotation is about weaving data into textual sources. In semantically annotated texts, certain words (denoting things, people, locations, organizations, etc) are linked to data – that is, to context and references that can be processed by an algorithm.
Read more in the article: Weaving Data Into Texts: The Value of Semantic Annotation.
As you can see, technology here lends us a helpful machine hand to the process of reading and organizing large volumes of textual resources, leaving our mind space and resources for creativity and synthesis.
At the end of the day, “a mechanical brain” will replace us not to think for us, but to compute for us, to connect billions of facts, discover relationships and unearth information from heaps of unstructured content.
The rest will still be all ours. Nothing more, nothing less. Just a cognitive enhancement powered by smart data.
Want to learn more about for smart data management?
White Paper: Text Analytics for Enterprise Use |
Learn how companies can tap into the power of the data coming their way by integrating the huge data flows with their proprietary data.
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Learn how companies can tap into the power of the data coming their way by integrating the huge data flows with their proprietary data.
Learn about FactForge and how you can turn the opportunities that data flows on the web can pour into our business into a real experience.
Learn how semantic technologies can bring audiences back to libraries and make library archives and collections visible and accessible.
Marketing Expert at Ontotext
Teodora is a philologist fascinated by the metamorphoses of text on the Web. Curious about our networked lives, she explores how the Semantic Web vision unfolds, transforming the possibilities of the written word. From 2022 on, Teodora helps with the creation and curation of the Ontotext knowledge graph to foster information ecology out of marketing content that will enable relevant user experiences across Ontotext's universe.
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Learn more about the importance of being metadata-driven today in our latest SlideShare presentation.
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