Communications - December 2009

Figure 2. all data/information can be linked in a mesh through relationships. Common, machine-processable formats are used to represent every aspect of a data mesh.

structured data at Web scale. Recent success stories in the application of knowledge representation to specific domains, as in the myGrid (see http:// www.mygrid.org.uk/) work in BioInformatics research, 10 demonstrate the potential benefits of semantic computing technologies. Here, we use the term “data mesh” to encompass the various concepts and approaches that could be used or combined to support a semantics-rich ecosystem of research tools and services. It is not our intention to suggest there would be one single data mesh that would represent all human knowledge.

We expect a great number of vocabularies to emerge, many of which will overlap, for representing every aspect of a data mesh (such as geo-location, mood, reviews, personal information, domain-specific concepts and terms). Ontologies will support an evolving ecosystem of facts, vocabularies, and relationships in specific domains. We are already witnessing a plethora of emerging efforts to standardize on such vocabularies, such as microformats ( http://www.microformats.org/), data portability (http://www.dataport- ability.org/), gene ontology (http:// www.geneontology.org/), and others.

Programs will consume, combine, and correlate everything in the universe of structured information and help users reason over it. They will allow them to ask questions against this (global) collection of facts— information access policies permitting—such as “Which is the most popular book among my friends today?,” “Who is the expert on aspect A of my business

workflow inside my organization?,” “Have Evelyne and Savas been at the same conference, at the same time in any point in time?,” “What’s the degree of separation in terms of citations between my paper and the seminal work by Jim Gray?” and so on.

While data mesh instances can be built in isolation (as in many of today’s social networks), we believe the potential value of aggregating all of them and combining them in one huge network of facts is tremendous. This idea is similar to Tim Berners-Lee’s more recent rhetoric around the ‘Giant Global Graph of Facts’ (see http://dig.csail.mit.edu/breadcrumbs/ node/215). Please note that we are not suggesting there would be a single repository of facts or that there would even be universal agreement on what is represented. We do expect, however, to see machine-based technologies

We are already
witnessing the
emergence of data
mesh instances
on the Web,
especially as
they relate to
social networks.

that would be able to reason, many times using probabilistic-based techniques, over the diverse set of facts.

We are already witnessing the emergence of data mesh instances on the Web, especially as they relate to social networks.Th e Zune Social (http://so- cial.zune.net/) is an example of how a social network can be combined with information about music preferences, recommendations, and an online marketplace. Facebook (http://www.face- book.com/) is another example of how connections between identities can help in aggregating user-oriented preferences and then inferring behavior and preference statistics. Finally, Pow-erset ( http://www.powerset.com/) is an example of a search service that leverages existing structured information, for example, Freebase (http://www. freebase.com/) or generates it from unstructured sources (such as by applying natural language processing technologies on Wikipedia content) to improve the quality of the query results.

We believe that over time, a huge ecosystem of services and tools will emerge around data mesh instances. Such tools and services will allow us to move beyond current practice of information management by incorporating more automation. Recommendation engines will be the norm and our interactions with computers will always be context-aware (for example, “since the topic of the paper being written is about botany, a query about ‘bush’ is unlikely to be about a person’s name” or “the search about papers on orchid will take into consideration the opinion of people in the user’s professional social network”). While today we can search for information over the global graph of linked Web pages consisting of predominately unstructured data, in the future we will be able to search over all types of semantically enriched information, which will in turn enable a wide range of new applications to emerge such as recommendation services, information management automation, information inferencing, and so forth.