Universal Repository
We all have the need to store and find information. The information might be as simple as a phone number or a to-do list. It might be more complex like a plan for a project or a sales order. Or it might be a huge, general knowledge base containing millions of data-sets.
On a personal level, when we need to store information we usually do that using dedicated apps like address books or general-purpose tools like spreadsheets; or we just write it down as plain text and save it somewhere, maybe as a file in our documents folder or cloud storage space. Corporation, governments and associations additionally use sophisticated information management systems like CRM, CMS, document stores, etc.
The problem with all these approaches: The scope in which that information can be used is limited. Unless plain text is used, the type and detail level of information that can be stored is limited to the features those applications provide. Using plain text on the other hand, limits the ability of computers to understand the contents and therefore makes it difficult for them to support humans analyzing and reusing those information. See The Semantic Problem, Universal KB and Universal Information for more details on these topics.
A universal repository is a semantic database for arbitrary information. Much like ordinary text, it accepts information without having to be prepared for any specific type; we just add information by expressing it using a graph language. But unlike ordinary text, it accepts information in any order, the sequence in which information is added to the repository is irrelevant because information expressed in a graph language is pure, independent of protocol and order.
In some ways, a universal repository is like a book; an author can write a story about anything imaginable without having to define any entity or relation-type that might occur in the story at the beginning of the book. A user can express any type of information at any detail and complexity level using a graph language and add it to the repository. But unlike the story in the book, which makes only sense if the letters and words it consist of are in a specific sequence, the order in which information is added to a universal repository does not matter. The information just becomes part of the repository, automatically merges with any related information.
Using a universal repository, we can store information independently of applications. This is potentially game changing. We are not limited to the features applications provide in terms of information we can store. Specific information need only to be entered one time, all applications can access the same data. Information can be universally exchanged between users; we are not limited by the interfaces apps are providing. We can very precisely decide what information an app can access, down to the smallest detail level. Universal repositories for Havel use multi-level encryption and information trustworthiness assessment, all our data is as secure and trustworthy as we require it.
A universal repository is an information database that traditional applications and services can query in order to retrieve and store information. Technically, it is most likely a Samarai brain and apps query it using one of its network communication interfaces. Using Samarai brains, there is always a separate layer between information and app, ensuring that data access rules set by the data owner are enforced.
Users have application-independent access to information using IMEs and NMEs. They can create new or alter existing information. Because of the universality of Havel, as long as they do not change the principal meaning of the information, apps should be able to accept the altered data.
In praxis, the repository can be a single Samarai brain with access to files containing Havel expressions or to an Alotau instance, running on a local device or in the cloud. But it could also be a homogeneous network of connected Samarai brains, each having access to a set of separate universal repositories, all together forming a semantic social network which acts as a universal repository to the outside.
Due to its semantic background, a universal repository based on a semantic social network can be regarded as a form of intelligent knowledge base. Distribution hubs can dispatch specific queries depending on content, forward requests to nodes that seem most likely to have answers depending on domain and context of the request. A request can be multiple times forwarded until an answer is found or in order to collect as much and diverse information as possible. The asynchronous nature of Samarai communications enables deferred replies for information that is not yet available in the repository, maybe awaiting human interaction. Collaborative computers can autonomously execute complex tasks as part of the requests.
This post is part of a comprehensive introduction into SRDM, graph languages and Havel.
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