During the implementation I ran into various issues as you can read in the validation for this proposal. Fortunately the Stanbol team was very helpful and Andrea and Alessandro helped a lot to get it working in the end. I made a 10 minutes video where I explain what I did with Stanbol and how we plan to use it in the future.

Thanks to the Stanbol team for the great work, netlabs.org keeps a close eye on Stanbol and will integrate parts of its stack into our framework!

The benchmark is designed to measure how well semantic features are already available in existing CMS. Additionally, it consists of a self-assessment survey for software developers to measure their own knowledge about software engineering concepts and technologies required for semantic applications.

We have created a dedicated website for this benchmark that will be maintained even after the project has ended. We would like to establish this online benchmark and refine it over the time based on user feedback. Therefore, this benchmark is open for everyone and free to use or reference. To make a great start we encourage everyone to invest a few minutes to answer it.

For CMS vendors:

• Get indicators for semantic features that may be relevant for you.
• Think about your current CMS and reflect how well it is prepared for a more semantic future.
• See public statistics of the survey.

For software developers:

• Measure your knowledge about semantic concepts.
• Get indicators to see what you should learn next.
• See public statistics of the survey.

The benchmark and more information are available at our new website.

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The first thing to establish in 2013 is a regular release cycle for all Apache Stanbol components. This is important to make it more easy for the users to rely on stable artifacts without any need to check out the sources and compile the system on their own. The project should manage to cut releases at least every four months.

Closely related to releases is the still existing licensing problem of some natural language processing models. For example, Apache Stanbol uses some models of the Apache OpenNLP project and it is still unclear which license applies to those models. So making Stanbol more independent of compiled-in model files with problematic licenses is another task to do.

Besides these tasks there is room for improvements. The Entityhub will get updated to use a two layered storage architecture (STANBOL-704) similar to the one proposed for the Contenthub in STANBOL-471. With this new storage architecture Apache Stanbol will be able to store any content separated from different semantic indexes for access. This allows users to create new types of views on their content based on different semantic indexes.

Additionally, the new storage architecture for the Entityhub allows to improve the step of entity disambiguation. Rupert Westenthaler reported on the Stanbol developer mailing list about three improvement for the entity disambiguation engine:

1. It will allow to to efficiently manage a “Shallow Knowledge Base (KB)” also for vocabularies that are managed in the Entityhub or by a managed site (see STANBOL-673), because batch processing with the Entityhub indexing tool will no longer be required to build a good ”Shallow KB”.
2. The separation of “entity store” and “entity index” (that is meant by “two layered”) will also allow to have several entity indexes for a single entity. This e.g. would also allow to build special indexes (e.g. a temporal and spacial index) that cover entities of several/all vocabularies. Those additional indexes could be than used to disambiguate along additional dimensions  what should improve the disambiguation results.
3. Entity indexes could also allow to collect entity information from different sources. This would allow to combine information available for the entity in the vocabulary with additional information  e.g. mentions of the entity as collected by some feedback service or available via annotated documents in the Contenthub. This would allow disambiguation to work on ”occurrence / mention-based” contexts.

Beside those improvements Apache Stanbol will have a close look at the technology that will be introduced by the new incubating project Apache Marmotta. With Apache Marmotta the Linked Data Server of the Linked Media Framework (LMF) becomes Apache software that can be used by Apache Stanbol. Additionally, the LMF already has an Apache Stanbol integration. The Linked Data Server could be an interesting component for the idea of a Factstore in Apache Stanbol that never reached a stable state. The Factstore in its current state will be removed from Apache Stanbol but with Marmotta there may be a new approach possible in 2013.

Other improvements to make Apache Stanbol more usable in industrial and productive contexts may also be coming in 2013. The Fusepool project announced that it will rely on Apache Stanbol and plans to contribute. We have already seen some discussions on the developer mailing list. The first contribution for more security aware coding in Apache Stanbol already hit the trunk. We will see what the future will bring. Exciting times for Stanbol!

This post outlines the current state of Create, and some of the things that will be happening around it in 2013.

Increased CMS adoption
Thanks to being picked up by major CMSs like Drupal 8, TYPO3 Neos, Midgard, Symfony CMF and OpenCms for their inline editing needs, Create.js is experiencing very strong adoption. Many of these CMSs will be shipping a new major version during 2013.

These releases will bring Create.js into millions of sites out there, giving users a friendlier and faster way to edit the web. By being built on the semantic interaction framework of VIE, this also means a significant expansion of the RDFa Linked Data base.

This amount of new users will be staggering, meaning that we will need to put a lot of focus into stability and ease-of-use of the toolkit. To make life for new integrators and contributors easier, we will also need to improve the documentation and test coverage. All of this is shown also by the fact that Create.js on GitHub has climbed from few hundred watchers a year ago to nearly 1400 today.

Read complete story…

This integration is the result of Manafactory’s participation in the IKS Early Adopters program and of a fruitful collaboration with INSIDEOUT10 (another IKS Early Adopter) – INSIDEOUT10 previously worked on WordPress (the same application framework Twistory uses) and added the contributed engines (a complete list is described in the validation page) we used for our scope.

Thanks to Apache Stanbol enhancement engines and to the gateway API that was developed for this project Twistory is now able to enrich tweets as well as web pages linked in those tweets with named entities (people, organizations and places) and to keep track of the resource consumption for these semantic enrichments in terms of calls, data processing units and generated traffic (these can be monitored here http://idntik.it/#/reports/calls). Twistory is available as Software as a Service Model (SaaS) therefore is important for us to keep track for each instance of the resource consumption.

Adding the semantic layer to Twistory at this stage provides users (Social Media Specialists) with a new way to organize the information on the system (tweets and links are now accessible by looking at people, organization and places) and to discover emergent patterns in the conversations (for instance the impact of the upcoming italian political elections in the links can be seen when looking at the list of the organizations).

Here we present a screencast of the trial we’re performing with ATAC SpA (one of our client – the Public Transport Agency for the city of Rome) that describes the semantic features of Twistory.

For this use-case we’re including in the monitoring a set of keyword to filter the incoming twitter firehose (these are: ATAC, MetroA, MetroB) – each tweet is annotated with relevant Freebase/DBpedia entities describing people, organizations and places – moreover for each link contained in these tweets a similar analysis is performed by fetching the URLs and removing any HTML tag with a Stanbol Façade (a custom API front-end for Stanbol that includes Rhino and Readability.js) that was developed for the scope.

The annotations are used to browse tweets and links and are visualized using a set of pie charts.