An #opensource #software framework to build Games with Purpose for #linkeddata refinement: Web applications to crowdsource partial ground truth, by motivating user participation through fun incentives #knowledgegraph #datascience #data #opendata #research

Representing Graph #Data Structures: Edge Lists, Adjacency Matrices, Adjacency Lists #datascience #analytics #tutorial #datamodel #softwareengineering #data #tech

This survey provides #knowledgegraph review: KG representation learning, knowledge acquisition & completion, temporal KG, KG #applications. It summarizes recent breakthroughs & perspective directions to facilitate future #research #AI #data h/t @aaranged

Recent #research proved #deeplearning can be used to learn RDFS inference rules. A deficiency: lack of derivations for inferred triples, or explainability in #AI terms. @IBMResearch @jahendler provide inferred graph, explain how triples were inferred

A blueprint for the next @apachetinkerpop and an analysis on #opensource. @twarko @_mmadt #presentation from @DataDayTexas #GraphDB #data #tech #cloud #insight #softwareengineering #softwaredevelopment #AWS

#Neo4j #GraphDB has added sharding @adamcowley shows when and how to use it #softwareengineering #data #tech #opensource #tutorial [LINK]https://adamcowley.co.uk/neo4j/sharding-neo4j-4.0/ [LINK]https://neo4j.com/docs/operations-manual/4.0-preview/images/fabric-single-instance.png

Fast, simple & flexible API for the #SchemaOrg Vocabulary (and vocabulary extensions!) for Node and Browsers #softwareengineering #SEO #semantics #data #tech #datascience #javascript h/t @OmarNicarao @aaranged [LINK]https://www.npmjs.com/package/schema-org-adapter [LINK]https://i.imgur.com/ULn1Y5I.png

LinkedSDGs: linking information resources & discovering connections to #SDGs 1) upload document 2) extract key concepts 3) find links to #SDGs & relevant stats #linkeddata & knowledge extraction resources @SustDev #opendata #data #tech #sustainability [LINK]https://www.linkedin.com/feed/update/urn:li:activity:6628584405906661376/ [LINK]https://media-exp1.licdn.com/dms/image/C5622AQELLgccoCKFCw/feedshare-shrink_800/0?e=1583366400&v=beta&t=pfry2nj7rsH7Ex5cOs36op-Wdn0Y1lyvsYVUhMzEj7k

Traditional #factcheck methods like #fakenews detection by experts don't match the volume of information available. This is where computational fact-checking becomes relevant. Given #KnowledgeGraph, knowledge corpus, fact (triple): is fact correct? #AI [LINK]https://dl.acm.org/doi/abs/10.1145/3371158.3371187 [LINK]https://pbs.twimg.com/media/EPVCXeIW4AAp87Y.jpg:large

The most depicted humans in #paintings #SPARQL query on #Wikidata looks an #artwork itself https://t.co/MgWi4bCDPo (ht @sanseveria ) pic.twitter.com/qMjZtNkCFM— Maarten Dammers (@mdammers) January 18, 2020

#Google #ProductSearch & Learning about New Product Lines. Patent analysis by @bill_slawski Google working hard to improve its product #knowledgegraph to compete with #Amazon by offering free / unpaid (non-ads) product results h/t @cyberandy #SEO #search [LINK]http://www.seobythesea.com/2020/01/new-product-lines/ [LINK]http://www.seobythesea.com/wp-content/poduct-search.jpg

An accurate representation of knowledge is essential for teaching systems. This #research gives insight into different knowledge representation techniques and their categorization into various problem domains in #AI #taxonomy #applications h/t @aaranged https://arxiv.org/abs/2001.04835

Weaviate #Knowledgegraphs. Difference between #database & #knowledgegraph @SeMI_tech on @GCPcloud stores KGs in a space, it's API-based, does auto-classification. Uses #opendata to train graph #machinelearning #cloud #opensource @markmirch @bobvanluijt [LINK]https://www.youtube.com/watch?v=SOUtWj2szOM&feature=emb_title [LINK]https://i.imgur.com/wG2P3yi.png

Property graphs seem inherently simpler. Semantic graphs put more emphasis on #datamodeling, treat node/edges as concepts bound by a universally unique identifier #data #tech #knowledgegraph #EmergingTech #datamodel #datascience #software @kurt_cagle [LINK]https://www.linkedin.com/pulse/state-graph-merger-property-graphs-semantic-kurt-cagle [LINK]https://media-exp1.licdn.com/dms/image/C5612AQF2DIFR7DjXKQ/article-cover_image-shrink_600_2000/0?e=1585785600&v=beta&t=tN9Z8ZbE1VeNHiPvhdFfDi34VwHW_pOHXPWv7Il8f7Q

Instead of representing #research in static PDF articles @l3s_luh works on a dynamic #knowledgegraph. The Open Research KG represents ideas, approaches, methods in machine-readable form. A comparison of different genome editing methods can be created

Song Cui and Dhananjay Shrouty | Software Engineers, Content KnowledgeInterest Taxonomy at PinterestWe recently began rolling out the beta version of Pinterest Trends, a new tool that gives a view...

.@Josh_Bersin has been writing about the explosion of #Skills #Ontology from Workday, Degreed, EdCast, etc. @CornerstoneInc, a Learning Management Systems provider, entered the game via acquisition of @Clustree #futureofwork #knowledgegraph #EmergingTech

.@CamSemantics announces Anzo #GraphDB v.2: RDF*, Custom SDK, Free Edition. "Imagine being able to do labeled properties, just like you do in Neo4j & other property graphs, but also have capability of RDF to help w ontologies & inferencing" #data #tech

Multi-model is a useful #technology for #enterprise #knowledgegraphs, say @arthurakeen @arangodb Benefits: streamlining multi-source #data to EKGs, increasing usability of EKG data for business, enabling greater scale, reducing EKG ecosystem footprint

Kurt Cagle is one of the advisors behind the SEMANTICS 2020 Conference. He is a writer, data scientist and futurist focused on the intersection of computer technologies and society. He is also the founder of Semantical, LLC, a smart data company. In this interview, Kurt shares with us some of his expertise and his vision for the new paths being opened by Semantic Technologies.

Most #machinelearning #algorithms work well w/ either text or structured #data. #Semantic data models can close the gap. Relationships between business/data objects can be made available for further analysis #knowledgegraph #AI #datascience #EmergingTech

While graph #tech #GraphDB graph computation will not be everything, true #digitaltransformation will only get underway once we begin building out #knowledgegraphs to mediate the hardest part of #datamanagement: integration #innovation #data #2020NewYear

#KnowledgeGraphs and their central role in #bigdata processing: Past, Present, and Future #keynote #presentation #research #AI #datascience #data @amit_p

datacommons.org isn’t a single thing, but rather a collection of #data & tools. These comprise a #knowledgegraph linking data from a number of open sources, supporting schemas, API to access data in the graph, graph browser, fact-check dataset @aaranged

To understand trends as they’re happening, @pinteresteng needs to understand content & categories. To do that, they built a taxonomy-based knowledge management system that enables content understanding in a highly efficient way #knowledgegraph #AI #data

Creating Graphs in Python using Networkx #dataviz #tutorial #datascience #data #tech

Graph Theory and #DataScience: A topic intro with the Bridges of Königsberg. Graph Theory can be used to represent and analyze a wide variety of network information, has numerous modern applications within Data Science #data #tech #software #algorithms

#Semantic #technology, decision intelligence, knowledge #datascience will be our companions in the next years, so it's recommended to start exploring #graphdatabases, #ontologies, knowledge representation systems #knowledgegraph #AI #2020NewYear #trends

Graph #Visualisation w @TerminusDB #opensource #GraphDB: Bike Share #Data #tutorial #softwaredevelopment

Meaning-First data modeling for #semantic #knowledgegraphs: a replacement to Structure-First modeling. The relational model was a great start for #datamanagement, but it is time to embrace a radical return to simplicity: Meaning-First data modeling #data