Why #DIYPlanetWalk? - The Pivot and the MVP

Timlynn and I have two projects in the Pacesetters/semi-final round of the Ashoka/LEGO #Play2Learn 'Re-imagine Learning' Challenge. These two projects are intimately inter-related as "means and ends" in the domain of LAM-based (Libraries, Archives, and Museums) social games that keep us engaged in preserving and exploring on-line digital collections of our cultural heritage.

Inside the FactMiners' Brain - Rainman Meet Sherlock

NOTE: In case you missed it, here is a link to a screencast of Kenny Bastani's webinar about using the Neo4j graph database in text classification and related Deep Learning applications. It's a fascinating introduction to some original work Kenny is doing that leverages the strengths of a property graph, in this case Neo4j, to do some Deep Learning text-mining and document classification.

Revisiting Robert Axelrod's Brilliant Ideas on Cooperation

Robert Axelrod and his two foundation-laying great books

Timlynn and I are intently focused on the incredible "serious fun" we and others are having as participants in the Ashoka/LEGO #Play2Learn - Re-imagine Learning Challenge. We're especially excited that both our projects made it to the Pacesetters Round of this global competition. Our entries are FactMiners – this site and project; the 'how' side of our activity – and The Softalk Apple Project – the 'what'/sandbox where we're doing FactMiners' applied research.

CIDOC-CRM Meet METS/ALTO - A Recipe for FactMiners 'Fact Clouds'

FactMiners.org is very pleased to announce that we are adopting METS/ALTO as the "drill down" metadata and file/data format specifications that will guide our DSL (Domain Specific Language) extensions of the CIDOC-CRM as part of the design of the Open Source FactMiners LAM-based social-game platform.

Karma to Take a LOD off FactMiners

Collage of photos of Karma is an amazing Open Source "multilingual" ontology-aware cross-model smart-mapper

Karma is an amazing Open Source "multilingual" ontology-aware cross-model smart-mapper providing "Rosetta Stone"-like powers to users coping with the ever-shifting publication of Linked Open Data (LOD). Karma is the evolving brilliant work from the incredible minds of the researcher-makers of the Information Sciences Institute at the University of Southern California. Karma will likely handle this critical component of the technology stack that implements the FactMiners social-game ecosystem.

MW2014 temp

Note: This is not really a blog post in its own right, just a "cheat sheet" with a fewe useful URLs and some Cypher queries so I will have something handy for "demo any where, any time" during the Museums and the Web 2014 conference.

http://gist.neo4j.org/?7817558
http://gist.neo4j.org/?8640853

http://www.cidoc-crm.org/comprehensive_intro.html

Wishlist: A Metamodel Partition in Neo4j Graph Database

There are many reasons I had to explore the embedded metamodel subgraph design pattern for Neo4j databases in the first series of FactMiners ecosystem design documents.

My interest is grounded in my experience in the 1990's developing a pair of complementary Distributed Smalltalk frameworks to do what we called "executable business models." The basic idea was that if we came up with a super-elegant metamodel about how to do business processes AND STUCK TO IT no matter what on the server/executing-model side of things then the Desktop Visualization framework could dynamically generate what customer/users mistook for "applications." We found INCREDIBLE leverage in design-to-implementation and stakeholder buy-in (as what we built made sense to them... it was their mental model embodied in software).

We can bring this kind of leverage to graph databases, and I hope Neo4j will be the pioneer leader in this, by coming up with a community standard for an embedded metamodel subgraph feature.

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