The Remarkable Discovery of Richard III: A Graph Theory Journey
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Chapter 1: Unearthing History
In August 2012, a mechanical digger began its task in a Leicester car park, surrounded by curious onlookers eager to witness something extraordinary. A blend of amateur and professional historians had pieced together clues suggesting that this site might be the final resting place of Richard III, the hunchbacked English monarch who met his demise at the Battle of Bosworth Field in 1485. Thanks to crowdfunding and donations, they secured funding and authorization for an archaeological dig at the local council's parking lot, generating immense excitement, though many archaeologists remained doubtful.
As the dig commenced, a curious letter "R" marked a specific spot in the car park, hinting at something significant. Despite its mystery, no one knew its true meaning.
To the amazement of the team, just hours into the excavation, they unearthed a skeleton exhibiting a pronounced curvature of the spine. This discovery marked the start of one of modern archaeology's most remarkable stories. The challenge lay in conclusively linking this skeleton, which displayed signs of scoliosis associated with Richard III, to the historical figure himself.
Through subsequent examinations, the skeletal remains were dated to the late 15th century, revealing a diet rich in meat and fish, further supporting the hypothesis that this could indeed be Richard III. However, the final piece of evidence they needed was DNA confirmation.
Finding a living descendant of Richard III's sister, who could be traced through a maternal lineage spanning 500 years, was no easy feat. This search led them to Michael Ibsen, a Canadian carpenter and furniture restorer in North London. A DNA swab from Ibsen matched perfectly with that extracted from the skeleton, confirming the identity of the remains.
On March 26, 2015, Richard III's exhumed body was ceremoniously reinterred at Leicester Cathedral, receiving full Church of England rites over 500 years after his death.
Chapter 2: The Role of Graph Theory
The lineage of Michael Ibsen, along with numerous other ancestral mysteries, has become much more accessible due to the advent of graph databases. Although these databases have been around since the 1960s in niche applications, they gained traction in enterprise technology around 2005. Unlike traditional relational databases that organize data in tables, graph databases are rooted in mathematical graph theory.
Each ‘node’ can represent an individual or an object, while ‘edges’ illustrate the relationships between these nodes, allowing for more versatile queries. For example, using a graph database, one can easily identify all individuals who have collaborated on publications.
Social media platforms like Facebook and LinkedIn leverage graph databases extensively. Here, edges connect users to their friends and interests, making it seamless to add features like reactions to posts by simply updating edge properties.
Genealogy is another domain profoundly enhanced by graph databases. Ancestry.com, for instance, utilizes nodes to store personal details (birthdates, marriages, photographs) and edges to depict familial relationships (parent, sibling).
Building and Utilizing Graph Databases
Graph databases are relatively easy to establish and configure, with several reputable products available, such as Neo4j. This database is particularly effective for applications where relationships are central to the analysis, processing queries faster and with greater adaptability than traditional databases.
Neo4j employs a straightforward query language, Cypher, which simplifies the learning curve for those familiar with graph theory. For instance, if you wanted to identify friends knowledgeable about Neo4j, your query might look like this:
MATCH (you {name:"You"})
MATCH (expert)-[:WORKED_WITH]->(db:Database {name:"Neo4j"})
MATCH path = shortestPath( (you)-[:FRIEND*..5]-(expert) )
RETURN db,expert,path
Setting up a graph database is especially beneficial when existing data can be restructured to reflect connections among individuals or objects. Potential sources of data might include collaboration records, email metadata, and project participation logs.
If you haven't yet explored graph databases, consider diving in to experience their capabilities firsthand. Imagine the potential for quickly tracing distant relatives or uncovering connections in expansive organizations!
Have you had any experience with graph databases? We welcome your thoughts and comments.
This video discusses Richard III’s remarkable discovery, focusing on the archaeological techniques used.
Professor Kevin Schürer explores the identification and implications of discovering the remains of Richard III.