Web of Data, which contains open, structured data sets consisting of factual knowledge that are linked.Almost one year ago we started a post series that presented three different webs that are all made for machines. Now it is time to connect those webs and look at examples of how they can be used. To recap, first we looked at the
Second was the Web of Identities, which is like the Web of Data, but for people data. Its ability protect one's privacy and to cope with data volatility differentiates it from the Web of Data. In the Web of Identities, it's people's social graphs that link one identity to another.
Third was the Web of Services, which makes services accessible and processable. Their semantic annotation makes them a part of this series of webs. Machines can be taught to autonomously detect, apply and replace a service, or even link them by chaining or orchestrating them to solve bigger problems or to achieve redundancy or scalability.
For the last several years, mashups have shown us that through APIs, amateur programmers and startups have the ability to access data and services and thereby create appealing new services at low cost and at a low entry barrier. Often, the interfaces are proprietary and lack a standardization so that mashup services are hardwired to data and service sources. If one puzzle piece fails, the whole service fails. Usually there are no fall-back mechanisms to automatically replace a data or service source on failure.
The three webs form the basis for tomorrow's mashup generation. All webs follow basic Web principles, such as modularization, de-centrality and simplicity, and provide accessibility and detectability. The openness and availability of data, people data and services pave the way to an interoperating ecosystem of companies serving the fragments of tomorrow's services.
What would you build with a Web of Data?" this time we ask: What would you build given all these webs? Feel free to contribute your own ideas in the comments section! Here are my app ideas.The following scenarios all utilize all three webs. Just like Richard MacManus asked "
Pretty Social Recommendations
Bob addresses a service that provides social recommendations, which is based on the webs. He queries "recommend books about Berlin for my mother for Christmas". The service analyzes his query and splits it to a chain of subtasks, which it starts to process.
From the Web of Data, the service gathers general (common sense) knowledge about the terms used in the query. Like this, the service learns that a book is an purchasable item, that Berlin is a city in Germany, and so forth. The service also semantically understands "books about Berlin" and queries the Web of Data for books covering Berlin or authors born or living in Berlin.
This initial book list must be filtered using individual and contextual parameters now: Given permission from Bob, his identity provider (IDP) is called to return his mother's Web ID (a Web ID is a standardized identifier linking to the user's profile at the IDP of trust) from his social graph.
The mother's IDP is called to access data about the the topic fields, books, and, Berlin, she is interested in. The IDP returns a set of information the mother granted access to her family. The data contains general interests, some book purchases, reviews, comments, ratings and some attention data that was recorded observing her reading articles online. The service continues by querying the mother's closest friends' IDPs to see if one of them liked or recommends books about Berlin, since friends' recommendations are the most valuable.
The service now searches and calls a ranking service from the Web of Services that can handle books, personal interests and recommendations as input criteria and returns a ranked list of books.
In order to find the best deals for the remaining books, the service now compares and bargains prices at several book stores via the Web of Services limiting to those that guarantee a delivery before December 24.
Finally, the list of books is augmented with prices from different stores and then presented to Bob. Bob selects a book and pays with a checkout service from the Web of Services.
Alice recently graduated from a university. She knows that she needs an insurance package but has no idea what it should consist of. She's heard of an intelligent insurance packaging brokerage system which she visits using her browser. She logs into the system with the Web ID she got from her IDP. From the Web of Identities, and with her permission, the system initiates a profile lookup to gather information needed for the components of the insurance package. This saves her precious time.
It queries for information like private address, marriage status, age and gender. Since it can't find her current income, it prompts her directly. From the Web of Data, the system now queries for her neighborhood's crime statistics for risk estimates. The system then looks up insurance services it can find on the Web of Services.
It configures the services with the knowledge gathered, selects the best offers and combines them to a personalized insurance package. The package consists of products from different insurers from around the globe. She signs the contracts through the broker and logs out with the satisfaction that she now is neither under- nor over-insured.
Further Application Areas
The webs can also be used to filter the real-time Web to individual and context-relevant content. Easy-to-use activity stream queries that are above the level of a single social platform become feasible like "filter by private friends nearby" or "filter by business contacts living in Wellington talking about the real-time Web". How about a pinch of sentiment analysis: "filter by my boss but only if he is really upset" or "filter by brand XY but only if the community is getting nasty".
Without a doubt these data and services sources can help to improve lots of existing services at low cost, including augmented reality or location-based services. Valuable knowledge can be provided for locations found on the Web of Data, friends can be displayed if they agreed to expose their location to the querying person via the Web of Identities, and so forth.
These are only a handful of thoughts for a whole new era of applications fueled by an open, linked and semantic basis for data and service sources. What applications can you think of? Or do you find all this creepy?