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Seriously - and who doesn't already have the Reddit app it's great. But sometimes you just want to read something q…
12 hours ago
The Right Way to Hold People Accountable
Accountability = delivering on a commitment.
1. clear expectations
2. clear capability (skills and resources to deliver)
3. clear measurement (milestones with measurable targets)
4. clear feedback (ongoing, 2-way)
5. clear consequences (repeat 1-4 if not clear enough, reward appropriately if goal achieved, release if 1-4 were clear but failed anyway)
management 
2 days ago
The Feynman Technique: The Best Way to Learn Anything
1. "explain like I'm 5"
2. review, go back to source material
3. organize and simplify
learning 
2 days ago
The Reverse Sear Is the Best Way to Cook a Steak, Period | The Food Lab | Serious Eats
Doneness Target Temp in Oven Final Target Temp Approx Time in Oven

Medium-Rare 115°F (46°C) 130°F (54°C) 25 to 30 minutes

Medium 125°F (52°C) 140°F (60°C) 30 to 35 minutes
food  recipes  cooking 
3 days ago
cgrand/enlive: a selector-based (à la CSS) templating and transformation system for Clojure
a selector-based (à la CSS) templating and transformation system for Clojure
clojure  html 
3 days ago
Kurt Vonnegut’s 8 Tips on How to Write a Great Story – Brain Pickings
Use the time of a total stranger in such a way that he or she will not feel the time was wasted.
Give the reader at least one character he or she can root for.
Every character should want something, even if it is only a glass of water.
Every sentence must do one of two things — reveal character or advance the action.
Start as close to the end as possible.
Be a Sadist. No matter how sweet and innocent your leading characters, make awful things happen to them-in order that the reader may see what they are made of.
Write to please just one person. If you open a window and make love to the world, so to speak, your story will get pneumonia.
Give your readers as much information as possible as soon as possible. To hell with suspense. Readers should have such complete understanding of what is going on, where and why, that they could finish the story themselves, should cockroaches eat the last few pages.
writing 
4 days ago
Software 2.0 - Andrej Karpathy - Medium
Neural networks are not just another classifier, they represent the beginning of a fundamental shift in how we write software. They are Software 2.0.

It turns out that a large portion of real-world problems have the property that it is significantly easier to collect the data (or more generally, identify a desirable behavior) than to explicitly write the program. In these cases, the programmers will split into two teams. The 2.0 programmers manually curate, maintain, massage, clean and label datasets; each labeled example literally programs the final system because the dataset gets compiled into Software 2.0 code via the optimization. Meanwhile, the 1.0 programmers maintain the surrounding tools, analytics, visualizations, labeling interfaces, infrastructure, and the training code.
ai  software  programming  machinelearning  thought-piece  article 
4 days ago
fast.ai Datasets | fast.ai course v3
Image classification (MNIST, CIFAR, etc), NLP, image localization
ai  datasets 
5 days ago
Sᴘᴀʀᴛᴀɴ Visualiser
This is a visualisation/simulation tool of the GoI-style programming language framework Sᴘᴀʀᴛᴀɴ, by Dan R. Ghica, Koko Muroya and Todd Waugh Ambridge. Visualiser implemented by Todd Waugh Ambridge (based on previous work by Steven Cheung, using graph-viz-d3-js for generating diagrams and lo-js for parsing).
visualization  programming  logic  diagrams  code  animation 
7 days ago
Physics Documents
Documents that answer questions that came up on a Physics Educators forum.
physics  blog  teaching  education  algorithms 
7 days ago
From Vision to Values: The Importance of Defining Your Core
Vision - The dream; a team's true north. Primary objective is to inspire and create a shared sense of purpose throughout the company.

Mission - Overarching objective of the organization; should be measurable, achievable, and ideally inspirational. Should not be used synonymously with a vision statement. A great mission statement is brief, easy to remember, minimizes the use of the word "and" (to prevent a laundry list), shouldn't require follow-up clarifying questions when first presented, and ideally proves to be uniquely identifiable to the company, i.e. wouldn't be confused for another company's mission.

Strategy - How a company navigates its competitive landscape (and the dynamics most heavily influencing that landscape, e.g. technology) to achieve its objectives. Not to be confused with tactics, which are the specific steps put into place to manifest the strategy. Can also state strategy as a series of strategic objectives to help make it more actionable. Requires clear understanding and definition of an organization's strengths and competitive advantages.

Objectives - Measurable goals aligned with mission and strategy -- the fewer and simpler the better. Key first principle: if you can't measure it, you can't fix it.

Priorities - Stack ranked list of tactics designed to help the company realize its objectives. Should start with the question, "If we could only do one thing, what would it be?" and the team should not move onto the next item on the list until that question has been resolved.

Culture - The company's personality, i.e. who you are as a company, and perhaps more importantly, who you aspire to be.

Values - The principles that guide the organization's day-to-day decisions; a defining component of your culture.
management  leadership  strategy 
7 days ago
FnO: The Function Ontology
The Function Ontology is a way to semantically declare and describe functions, without depending on the implementation.

Decent concept but implementation is suspect. Named functions is very dicey without stable identifiers across versions like in Erlang/OTP or similar. And how about validating the results? String to String is a crapshoot, should have built-in pre- and post-conditions. This is in the territory of a distributed programming language and runtime, simple named functions are not going to cut it.
rdf  semantic  functional 
7 days ago
Validatrr
A validation approach using rule-based reasoning.
rdf  semantic 
8 days ago
RML.io
Generate knowledge graphs

The RMLMapper and the RMLStreamer are applications for Linux, Windows, and macOS machines for generating knowledge graphs. They both rely on declarative rules that define how the knowledge graphs are generated.

See also RMLEditor (https://rml.io/tools/rmleditor) and Matey (https://rml.io/yarrrml/matey)
knowledgegraph  data  rdf 
8 days ago
Squerall to SANSA-DataLake – SANSA-Stack
See https://eis-bonn.github.io/Squerall/

An implementation of the so-called Semantic Data Lake, using Apache Spark and Presto. Semantic Data Lake is a Data Lake accessed using Semantic Web technologies: ontologies and query language (SPARQL).

Currently supported data sources:

Evaluated: CSV, Parquet, MongoDB, Cassandra, JDBC (MySQL, SQL Server, etc.).
Experimental: Elasticsearch, Couchbase. You can extend Squerall to support more
datalake  datawarehouse  sparql  semantic  knowledgegraph 
8 days ago
linkedgeodata.org - Adding a spatial dimension to the Web of Data
LinkedGeoData is an effort to add a spatial dimension to the Web of Data / Semantic Web. LinkedGeoData uses the information collected by the OpenStreetMap project and makes it available as an RDF knowledge base according to the Linked Data principles. It interlinks this data with other knowledge bases in the Linking Open Data initiative.
semanticweb  linkeddata  geo  rdf  data 
8 days ago
AllenNLP
An open-source NLP research library, built on PyTorch
View Demo
pytorch  nlp  ai 
8 days ago
Linked Data Fragments
650,000+ linked data datasets. Federated search against live linked data; does something smart distributing work between client and server. Comunica is the reference client. Can query against SPAQRL endpoints, various RDF dumps, HDT dumps, and more.
rdf  linked-data  linkeddata  search  sparql  semantic 
8 days ago
SANSA-Stack – Scalable Semantic Analytics Stack - Open Source Algorithms for Distributed Data Processing for Large-scale RDF Knowledge Graphs
SANSA is a big data engine for scalable processing of large-scale RDF data. SANSA uses Spark and Flink which offer fault-tolerant, highly available and scalable approaches toefficiently process massive sized datasets. SANSA provides the facilities for Semantic data representation, Querying, Inference, and Analytics.

SANSA-Stack’s core is a processing data flow engine that provides data distribution and fault tolerance for distributed computations over RDF large-scale datasets.

SANSA includes several libraries for creating applications:

Read / Write RDF / OWL library for RDF/OWL operations,
Querying library support a query language on top of distributed RDF/OWL library, as well as querying heterogeneous non-RDF data.
Inference library implements rule-based reasoning on RDF/OWL data,
ML- Machine Learning core library

SANSA is easily integrated with well-known open source systems both for data input and output (HDFS) and is build on top of Spark and Flink.
rdf  bigdata  semantic  knowledgegraph 
8 days ago
LOD-a-lot
LOD-a-lot democratizes the access to the Linked Open Data (LOD) Cloud by serving more than 28 billion unique triples from 650K datasets (collected in LOD Laundromat) from a single self-indexed HDT file.

This corpus can be queried online with a sustainable Linked Data Fragments interface, or downloaded and consumed locally.
data  datasets  linked-data  linkeddata  search  semantic  rdf 
8 days ago
Tarql: SPARQL for Tables – Tarql – SPARQL for Tables: Turn CSV into RDF using SPARQL syntax
Tarql is a command-line tool for converting CSV files to RDF using SPARQL 1.1 syntax. It’s written in Java and based on Apache ARQ.

Here's a version with HDT support https://github.com/rdfhdt/tarql
csv  sparql  linkeddata  rdf  cli 
8 days ago
LOD Laundromat
The LOD Laundromat provides access to all Linked Open Data (LOD) in the world. It does this by crawling the LOD cloud, and converting all its contents in a standards-compliant way (gzipped N-Triples), removing all data stains such as syntax errors, duplicates, and blank nodes.
linkeddata  linked-data  opendata  dataset  rdf  search  searchengine 
8 days ago
GERBIL — Agile Knowledge Engineering and Semantic Web (AKSW)
GERBIL is a general Linked Data benchmarking system (formerly used for entity annotation systems based on the BAT-Framework). GERBIL offers an easy-to-use web-based platform for the agile comparison of annotators using multiple datasets and uniform measuring approaches. To add a tool to GERBIL, all the end user has to do is to provide a URL to a REST interface to its tool which abides by a given specification. The integration and benchmarking of the tool against user-specified datasets is then carried out automatically by the GERBIL platform.

We also used GERBIL for benchmarking system for question answering
semantic  semanticweb  knowledge  linkeddata  testing 
8 days ago
FAIR Principles - GO FAIR
Findable, accessible, interoperable, reusable
data  framework  principles  metadata 
8 days ago
NERD: Named Entity Recognition and Disambiguation
The NERD ontology is a set of mappings established manually between the taxonomies of named entity types. Concepts included in the NERD ontology are collected from different schema types: DBpedia ontology (for DBpedia Spotlight and Lupedia), lightweight taxonomies (for AlchemyAPI, Yahoo!, Wikimeta, and Zemanta) or simple flat type lists (for Extractiv, OpenCalais, Saplo, Semitags). The NERD ontology tries to merge the linguistic community needs and the logician community ones: we developed a core set of axioms based on the Quaero schema which define the NERD core and we mapped similar concepts described in the other scheme. The selection of these concepts has been done considering the greatest common denominator among them. The concepts that do not appear in the NERD namespace are sub-classes of parents that end-up in the NERD ontology. To summarize, a concept is included in the NERD ontology as soon as there are at least three extractors that use it.
ontology  rdf 
8 days ago
dice-group/gerbil: GERBIL - General Entity annotatoR Benchmark
This project is a benchmarking platform for entity annotation and disambiguation tools. It also has been extended for Question Answering
nlp 
8 days ago
TAGME: on-the-fly annotation of short text fragments!
TAGME is a powerful tool that is able to identify on-the-fly meaningful short-phrases (called "spots") in an unstructured text and link them to a pertinent Wikipedia page in a fast and effective way. This annotation process has implications which go far beyond the enrichment of the text with explanatory links because it concerns with the contextualization and, in some way, the understanding of the text.

Code: https://github.com/gammaliu/tagme
nlp  ner 
8 days ago
T-REx : A Large Scale Alignment of Natural Language with Knowledge Base Triples
Enormous dataset of extracted triples from DBpedia, WikiData, and other sources. Code included as well.
nlp  knowledgegraph  rdf  knowledge  datasets 
8 days ago
The four layers of communication in a functional team — Quartz at Work
1. A mission (also known as a vision)
2. Strategy (made up of proximate objectives)
3. Tactics and process
4. Execution


Overall good, vision and mission are different though. Vision is long-term concept of the world that you see in the future. Mission is what you're doing today to move toward the vision.
communication  strategy  leadership  tactics  management  culture 
9 days ago
niceideas.ch: The Lean Startup - A focus on Practices
Decent overview of Four Steps to the Epiphany and Lean Startup concepts, careful of dogma though.
startups  process  diagrams  product-development  strategy  guide 
10 days ago
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