What is an application network? And why does it need a graph? MuleSoft's founder and CTO help explain today's announcement at Dreamforce 2018

Discover a new way to visualize and explore your connected data with SemSpect: a unique approach to graph visualization that doesn't depend on using random or best-guess Cypher queries in order to explore your data's meta-graph and that is compatible with Neo4j (including RDF datasets).

Learn how to use Neo4j to integrate a BigQuery public dataset with Stackdriver logs into a graph database, to surface new conclusions from complex data.

An evaluator's task is to connect the dots between program goals and its outcomes. This can be accomplished through surveys, research, and interviews, and is frequently performed post hoc. Research evaluation is hampered by a lack of data that clearly connect a research program with its outcomes and, in particular, by ambiguity about who has participated in the program and what contributions they have made. Manually making these connections is very labor-intensive, and algorithmic matching introduces errors and assumptions that can distort results. In this paper, we discuss the use of ident...

Graphs are a general-purpose #datamodel, as relational was a general-purpose #data model a generation ago. A supply chain is a graph. Knowledge is a graph. Graphs are very applicable in a wide range of use cases @jimwebber @TheRegister #GraphDB #tech [LINK]https://www.theregister.co.uk/2020/02/05/graph_database_neo4j_chief_scientist/ [LINK]https://regmedia.co.uk/2016/04/26/graph_database.jpg

Optimizing #algorithms on large scale labeled property graphs. Comparing optimization approaches, directly querying #graphdatabase. Aim: determine limiting factors of #GraphDBs. Speedup of a factor between 44 & 3839 #knowledgegraph #research #EmergingTech [LINK]https://arxiv.org/abs/2002.03686 [LINK]https://i.imgur.com/75Wxc5b.png

Mbabel #bot automatically generates article drafts based on information stored in #Wikidata. It puts generated content on a “user test page on Wikipedia”; users can expand it. Quality is influenced by heavy reliance on Wikidata #AI #opendata #semantics [LINK]https://www.vice.com/en_us/article/4agamm/the-worlds-second-largest-wikipedia-is-written-almost-entirely-by-one-bot [LINK]http://video-images.vice.com/articles/5e3c6732c62ac8009d1e9f27/lede/1581016882789-1_31_2020_THE_SECOND_LARGEST_WIKIPEDIA_SECTION_WRITTEN_BY_ONE_BOT_CV_ALT.jpeg

Building on the newbie’s guide to querying #Wikidata, @markhneedham learns all about the CONSTRUCT clause in SPARQL #softwareengineering #datascience #tutorial #opendata #linkeddata #knowledgegraph #GraphDB #data #tech

#SchemaOrg created FAQ Schema. #Google introduced filtering parameters that come w Search implementation. These act as commandments for Google’s algorithm which should be abided by for when markup is used in search results #SEO #semantics h/t @cyberandy

An Introduction to #Ontology Engineering: Version 1.5 of the textbook now available online #knowledgegraph #datamodel #tutorial #data #tech #datascience h/t @aarranged

#Knowledgegraphs are a natural fit for knowledge management: they model domains to retain more context & meaning even as information is parsed and abstracted for digital representation. Information is modeled in a way that is more intuitive & useful

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...