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Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson and others

Posted in Computational Biology/Systems and Bioinformatics, Curation, Curation methodology, Dialectic, Discovery process, Experimental validation, Explanatory, Health Economics and Outcomes Research, HealthCare IT, Open Access Journals, Pharmaceutical Industry Competitive Intelligence, Scientist: Career considerations, Scoop.it, Statistical Methods for Research Evaluation, Technology Advance Assessment of, Theoretic convergence, Uncategorized, tagged #science2_0, @science 2_0, Aviva Lev-Ari, collaboration, Conditions and Diseases, Content Curation, Curation, curation communities, Curation methodology, Curator, health, Larry H. Bernstein, medical literature, medical news, medical reporting, medicine, Open Access Online Scientific Journal, Open Access Publishing, Open data, science, Scientific literature, scientific networks, scientific news, Social network on July 17, 2014| Leave a Comment »

Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson

Curators and Writer: Stephen J. Williams, Ph.D. with input from Curators Larry H. Bernstein, MD, FCAP, Dr. Justin D. Pearlman, MD, PhD, FACC and Dr. Aviva Lev-Ari, PhD, RN

(this discussion is in a three part series including:

Using Scientific Content Curation as a Method for Validation and Biocuration

Using Scientific Content Curation as a Method for Open Innovation)

Every month I get my Wired Magazine (yes in hard print, I still like to turn pages manually plus I don’t mind if I get grease or wing sauce on my magazine rather than on my e-reader) but I always love reading articles written by Clive Thompson. He has a certain flair for understanding the techno world we live in and the human/technology interaction, writing about interesting ways in which we almost inadvertently integrate new technologies into our day-to-day living, generating new entrepreneurship, new value. He also writes extensively about tech and entrepreneurship.

October 2013 Wired article by Clive Thompson, entitled “How Successful Networks Nurture Good Ideas: Thinking Out Loud”, describes how the voluminous writings, postings, tweets, and sharing on social media is fostering connections between people and ideas which, previously, had not existed. The article was generated from Clive Thompson’s book Smarter Than you Think: How Technology is Changing Our Minds for the Better.Tom Peters also commented about the article in his blog (see here).

Clive gives a wonderful example of Ory Okolloh, a young Kenyan-born law student who, after becoming frustrated with the lack of coverage of problems back home, started a blog about Kenyan politics. Her blog not only got interest from movie producers who were documenting female bloggers but also gained the interest of fellow Kenyans who, during the upheaval after the 2007 Kenyan elections, helped Ory to develop a Google map for reporting of violence (http://www.ushahidi.com/, which eventually became a global organization using open-source technology to affect crises-management. There are a multitude of examples how networks and the conversations within these circles are fostering new ideas. As Clive states in the article:

Our ideas are PRODUCTS OF OUR ENVIRONMENT.

They are influenced by the conversations around us.

However the article got me thinking of how Science 2.0 and the internet is changing how scientists contribute, share, and make connections to produce new and transformative ideas.

But HOW MUCH Knowledge is OUT THERE?

Clive’s article listed some amazing facts about the mountains of posts, tweets, words etc. out on the internet EVERY DAY, all of which exemplifies the problem:

154.6 billion EMAILS per DAY
400 million TWEETS per DAY
1 million BLOG POSTS (including this one) per DAY
2 million COMMENTS on WordPress per DAY
16 million WORDS on Facebook per DAY
TOTAL 52 TRILLION WORDS per DAY

As he estimates this would be 520 million books per DAY (book with average 100,000 words).

A LOT of INFO. But as he suggests it is not the volume but how we create and share this information which is critical as the science fiction writer Theodore Sturgeon noted “Ninety percent of everything is crap” AKA Sturgeon’s Law.

Internet live stats show how congested the internet is each day (http://www.internetlivestats.com/). Needless to say Clive’s numbers are a bit off. As of the writing of this article:

2.9 billion internet users
981 million websites (only 25,000 hacked today)
128 billion emails
385 million Tweets
> 2.7 million BLOG posts today (including this one)

The Good, The Bad, and the Ugly of the Scientific Internet (The Wild West?)

So how many science blogs are out there? Well back in 2008 “grrlscientist” asked this question and turned up a total of 19,881 blogs however most were “pseudoscience” blogs, not written by Ph.D or MD level scientists. A deeper search on Technorati using the search term “scientist PhD” turned up about 2,000 written by trained scientists.

So granted, there is a lot of

….. when it comes to scientific information on the internet!

I had recently re-posted, on this site, a great example of how bad science and medicine can get propagated throughout the internet:

http://pharmaceuticalintelligence.com/2014/06/17/the-gonzalez-protocol-worse-than-useless-for-pancreatic-cancer/

and in a Nature Report:Stem cells: Taking a stand against pseudoscience

http://www.nature.com/news/stem-cells-taking-a-stand-against-pseudoscience-1.15408

Drs.Elena Cattaneo and Gilberto Corbellini document their long, hard fight against false and invalidated medical claims made by some “clinicians” about the utility and medical benefits of certain stem-cell therapies, sacrificing their time to debunk medical pseudoscience.

Using Curation and Science 2.0 to build Trusted, Expert Networks of Scientists and Clinicians

Establishing networks of trusted colleagues has been a cornerstone of the scientific discourse for centuries. For example, in the mid-1640s, the Royal Society began as:

“a meeting of natural philosophers to discuss promoting knowledge of the

natural world through observation and experiment”, i.e. science.

The Society met weekly to witness experiments and discuss what we

would now call scientific topics. The first Curator of Experiments

was Robert Hooke.”

– from The History of the Royal Society

The Royal Society of London for Improving Natural Knowledge.

(photo credit: Royal Society)

(Although one wonders why they met “in-cognito”)

Indeed as discussed in “Science 2.0/Brainstorming” by the originators of OpenWetWare, an open-source science-notebook software designed to foster open-innovation, the new search and aggregation tools are making it easier to find, contribute, and share information to interested individuals. This paradigm is the basis for the shift from Science 1.0 to Science 2.0. Science 2.0 is attempting to remedy current drawbacks which are hindering rapid and open scientific collaboration and discourse including:

Slow time frame of current publishing methods: reviews can take years to fashion leading to outdated material
Level of information dissemination is currently one dimensional: peer-review, highly polished work, conferences
Current publishing does not encourage open feedback and review
Published articles edited for print do not take advantage of new web-based features including tagging, search-engine features, interactive multimedia, no hyperlinks
Published data and methodology incomplete
Published data not available in formats which can be readably accessible across platforms: gene lists are now mandated to be supplied as files however other data does not have to be supplied in file format

(put in here a brief blurb of summary of problems and why curation could help)

Curation in the Sciences: View from Scientific Content Curators Larry H. Bernstein, MD, FCAP, Dr. Justin D. Pearlman, MD, PhD, FACC and Dr. Aviva Lev-Ari, PhD, RN

Curation is an active filtering of the web’s and peer reviewed literature found by such means – immense amount of relevant and irrelevant content. As a result content may be disruptive. However, in doing good curation, one does more than simply assign value by presentation of creative work in any category. Great curators comment and share experience across content, authors and themes. Great curators may see patterns others don’t, or may challenge or debate complex and apparently conflicting points of view. Answers to specifically focused questions comes from the hard work of many in laboratory settings creatively establishing answers to definitive questions, each a part of the larger knowledge-base of reference. There are those rare “Einstein’s” who imagine a whole universe, unlike the three blind men of the Sufi tale. One held the tail, the other the trunk, the other the ear, and they all said this is an elephant!
In my reading, I learn that the optimal ratio of curation to creation may be as high as 90% curation to 10% creation. Creating content is expensive. Curation, by comparison, is much less expensive.

– Larry H. Bernstein, MD, FCAP

Curation is Uniquely Distinguished by the Historical Exploratory Ties that Bind –Larry H. Bernstein, MD, FCAP

The explosion of information by numerous media, hardcopy and electronic, written and video, has created difficulties tracking topics and tying together relevant but separated discoveries, ideas, and potential applications. Some methods to help assimilate diverse sources of knowledge include a content expert preparing a textbook summary, a panel of experts leading a discussion or think tank, and conventions moderating presentations by researchers. Each of those methods has value and an audience, but they also have limitations, particularly with respect to timeliness and pushing the edge. In the electronic data age, there is a need for further innovation, to make synthesis, stimulating associations, synergy and contrasts available to audiences in a more timely and less formal manner. Hence the birth of curation. Key components of curation include expert identification of data, ideas and innovations of interest, expert interpretation of the original research results, integration with context, digesting, highlighting, correlating and presenting in novel light.

– Justin D Pearlman, MD, PhD, FACC from The Voice of Content Consultant on The Methodology of Curation in Cardiovascular Original Research: Cases in Methodology Design for Content Co-Curation The Art of Scientific & Medical Curation

In Power of Analogy: Curation in Music, Music Critique as a Curation and Curation of Medical Research Findings – A Comparison, Drs. Larry Bernstein and Aviva Lev-Ari likens the medical and scientific curation process to curation of musical works into a thematic program:

Work of Original Music Curation and Performance:

Music Review and Critique as a Curation

Work of Original Expression what is the methodology of Curation in the context of Medical Research Findings Exposition of Synthesis and Interpretation of the significance of the results to Clinical Care

… leading to new, curated, and collaborative works by networks of experts to generate (in this case) ebooks on most significant trends and interpretations of scientific knowledge as relates to medical practice.

In Summary: How Scientific Content Curation Can Help

Given the aforementioned problems of:

I. the complex and rapid deluge of scientific information

II. the need for a collaborative, open environment to produce transformative innovation

III. need for alternative ways to disseminate scientific findings

CURATION MAY OFFER SOLUTIONS

I. Curation exists beyond the review: curation decreases time for assessment of current trends adding multiple insights, analyses WITH an underlying METHODOLOGY (discussed below) while NOT acting as mere reiteration, regurgitation

II. Curation providing insights from WHOLE scientific community on multiple WEB 2.0 platforms

III. Curation makes use of new computational and Web-based tools to provide interoperability of data, reporting of findings (shown in Examples below)

Therefore a discussion is given on methodologies, definitions of best practices, and tools developed to assist the content curation community in this endeavor.

Methodology in Scientific Content Curation as Envisioned by Aviva lev-Ari, PhD, RN

At Leaders in Pharmaceutical Business Intelligence, site owner and chief editor Aviva lev-Ari, PhD, RN has been developing a strategy “for the facilitation of Global access to Biomedical knowledge rather than the access to sheer search results on Scientific subject matters in the Life Sciences and Medicine”. According to Aviva, “for the methodology to attain this complex goal it is to be dealing with popularization of ORIGINAL Scientific Research via Content Curation of Scientific Research Results by Experts, Authors, Writers using the critical thinking process of expert interpretation of the original research results.” The following post:

Cardiovascular Original Research: Cases in Methodology Design for Content Curation and Co-Curation

http://pharmaceuticalintelligence.com/2013/07/29/cardiovascular-original-research-cases-in-methodology-design-for-content-curation-and-co-curation/

demonstrate two examples how content co-curation attempts to achieve this aim and develop networks of scientist and clinician curators to aid in the active discussion of scientific and medical findings, and use scientific content curation as a means for critique offering a “new architecture for knowledge”. Indeed, popular search engines such as Google, Yahoo, or even scientific search engines such as NCBI’s PubMed and the OVID search engine rely on keywords and Boolean algorithms …

which has created a need for more context-driven scientific search and discourse.

In Science and Curation: the New Practice of Web 2.0, Célya Gruson-Daniel (@HackYourPhd) states:

To address this need, human intermediaries, empowered by the participatory wave of web 2.0, naturally started narrowing down the information and providing an angle of analysis and some context. They are bloggers, regular Internet users or community managers – a new type of profession dedicated to the web 2.0. A new use of the web has emerged, through which the information, once produced, is collectively spread and filtered by Internet users who create hierarchies of information.

.. where Célya considers curation an essential practice to manage open science and this new style of research.

As mentioned above in her article, Dr. Lev-Ari represents two examples of how content curation expanded thought, discussion, and eventually new ideas.

Curator edifies content through analytic process = NEW form of writing and organizations leading to new interconnections of ideas = NEW INSIGHTS

i) Evidence: curation methodology leading to new insights for biomarkers

Same as #1 but multiple players (experts) each bringing unique insights, perspectives, skills yielding new research = NEW LINE of CRITICAL THINKING

ii) Evidence: co-curation methodology among cardiovascular experts leading to cardiovascular series ebooks

The Life Cycle of Science 2.0. Due to Web 2.0, new paradigms of scientific collaboration are rapidly emerging. Originally, scientific discovery were performed by individual laboratories or “scientific silos” where the main method of communication was peer-reviewed publication, meeting presentation, and ultimately news outlets and multimedia. In this digital era, data was organized for literature search and biocurated databases. In an era of social media, Web 2.0, a group of scientifically and medically trained “curators” organize the piles of data of digitally generated data and fit data into an organizational structure which can be shared, communicated, and analyzed in a holistic approach, launching new ideas due to changes in organization structure of data and data analytics.

The result, in this case, is a collaborative written work above the scope of the review. Currently review articles are written by experts in the field and summarize the state of a research are. However, using collaborative, trusted networks of experts, the result is a real-time synopsis and analysis of the field with the goal in mind to

INCREASE THE SCIENTIFIC CURRENCY.

For detailed description of methodology please see Cardiovascular Original Research: Cases in Methodology Design for Content Co-Curation The Art of Scientific & Medical Curation

In her paper, Curating e-Science Data, Maureen Pennock, from The British Library, emphasized the importance of using a diligent, validated, and reproducible, and cost-effective methodology for curation by e-science communities over the ‘Grid’:

“The digital data deluge will have profound repercussions for the infrastructure of research and beyond. Data from a wide variety of new and existing sources will need to be annotated with metadata, then archived and curated so that both the data and the programmes used to transform the data can be reproduced for use in the future. The data represent a new foundation for new research, science, knowledge and discovery”

— JISC Senior Management Briefing Paper, The Data Deluge (2004)

As she states proper data and content curation is important for:

Post-analysis
Data and research result reuse for new research
Validation
Preservation of data in newer formats to prolong life-cycle of research results

However she laments the lack of

Funding for such efforts
Training
Organizational support
Monitoring
Established procedures

Tatiana Aders wrote a nice article based on an interview with Microsoft’s Robert Scoble, where he emphasized the need for curation in a world where “Twitter is the replacement of the Associated Press Wire Machine” and new technologic platforms are knocking out old platforms at a rapid pace. In addition he notes that curation is also a social art form where primary concerns are to understand an audience and a niche.

Indeed, part of the reason the need for curation is unmet, as writes Mark Carrigan, is the lack of appreciation by academics of the utility of tools such as Pinterest, Storify, and Pearl Trees to effectively communicate and build collaborative networks.

And teacher Nancy White, in her article Understanding Content Curation on her blog Innovations in Education, shows examples of how curation in an educational tool for students and teachers by demonstrating students need to CONTEXTUALIZE what the collect to add enhanced value, using higher mental processes such as:

Knowledge
Comprehension
Application
Analysis
Synthesis
Evaluation

A GREAT table about the differences between Collecting and Curating by Nancy White at http://d20innovation.d20blogs.org/2012/07/07/understanding-content-curation/

University of Massachusetts Medical School has aggregated some useful curation tools at http://esciencelibrary.umassmed.edu/data_curation

Although many tools are related to biocuration and building databases but the common idea is curating data with indexing, analyses, and contextual value to provide for an audience to generate NETWORKS OF NEW IDEAS.

See here for a curation of how networks fosters knowledge, by Erika Harrison on ScoopIt

(http://www.scoop.it/t/mobilizing-knowledge-through-complex-networks)

“Nowadays, any organization should employ network scientists/analysts who are able to map and analyze complex systems that are of importance to the organization (e.g. the organization itself, its activities, a country’s economic activities, transportation networks, research networks).”

– Andrea Carafa insight from World Economic Forum New Champions 2012 “Power of Networks”

Creating Content Curation Communities: Breaking Down the Silos!

An article by Dr. Dana Rotman “Facilitating Scientific Collaborations Through Content Curation Communities” highlights how scientific information resources, traditionally created and maintained by paid professionals, are being crowdsourced to professionals and nonprofessionals in which she termed “content curation communities”, consisting of professionals and nonprofessional volunteers who create, curate, and maintain the various scientific database tools we use such as Encyclopedia of Life, ChemSpider (for Slideshare see here), biowikipedia etc. Although very useful and openly available, these projects create their own challenges such as

information integration (various types of data and formats)
social integration (marginalized by scientific communities, no funding, no recognition)

The authors set forth some ways to overcome these challenges of the content curation community including:

standardization in practices
visualization to document contributions
emphasizing role of information professionals in content curation communities
maintaining quality control to increase respectability
recognizing participation to professional communities
proposing funding/national meeting – Data Intensive Collaboration in Science and Engineering Workshop

A few great presentations and papers from the 2012 DICOSE meeting are found below

Judith M. Brown, Robert Biddle, Stevenson Gossage, Jeff Wilson & Steven Greenspan. Collaboratively Analyzing Large Data Sets using Multitouch Surfaces. (PDF) NotesForBrown

Bill Howe, Cecilia Aragon, David Beck, Jeffrey P. Gardner, Ed Lazowska, Tanya McEwen. Supporting Data-Intensive Collaboration via Campus eScience Centers. (PDF) NotesForHowe

Kerk F. Kee & Larry D. Browning. Challenges of Scientist-Developers and Adopters of Existing Cyberinfrastructure Tools for Data-Intensive Collaboration, Computational Simulation, and Interdisciplinary Projects in Early e-Science in the U.S.. (PDF) NotesForKee

Ben Li. The mirages of big data. (PDF) NotesForLi ReflectionsByBen

Betsy Rolland & Charlotte P. Lee. Post-Doctoral Researchers’ Use of Preexisting Data in Cancer Epidemiology Research. (PDF) NoteForRolland

Dana Rotman, Jennifer Preece, Derek Hansen & Kezia Procita. Facilitating scientific collaboration through content curation communities. (PDF) NotesForRotman

Nicholas M. Weber & Karen S. Baker. System Slack in Cyberinfrastructure Development: Mind the Gaps. (PDF) NotesForWeber

Indeed, the movement of Science 2.0 from Science 1.0 had originated because these “silos” had frustrated many scientists, resulting in changes in the area of publishing (Open Access) but also communication of protocols (online protocol sites and notebooks like OpenWetWare and BioProtocols Online) and data and material registries (CGAP and tumor banks). Some examples are given below.

Open Science Case Studies in Curation

1. Open Science Project from Digital Curation Center

This project looked at what motivates researchers to work in an open manner with regard to their data, results and protocols, and whether advantages are delivered by working in this way.

The case studies consider the benefits and barriers to using ‘open science’ methods, and were carried out between November 2009 and April 2010 and published in the report Open to All? Case studies of openness in research. The Appendices to the main report (pdf) include a literature review, a framework for characterizing openness, a list of examples, and the interview schedule and topics. Some of the case study participants kindly agreed to us publishing the transcripts. This zip archive contains transcripts of interviews with researchers in astronomy, bioinformatics, chemistry, and language technology.

see: Pennock, M. (2006). “Curating e-Science Data”. DCC Briefing Papers: Introduction to Curation. Edinburgh: Digital Curation Centre. Handle: 1842/3330. Available online: http://www.dcc.ac.uk/resources/briefing-papers/introduction-curation– See more at: http://www.dcc.ac.uk/resources/briefing-papers/introduction-curation/curating-e-science-data#sthash.RdkPNi9F.dpuf

2. cBIO -cBio’s biological data curation group developed and operates using a methodology called CIMS, the Curation Information Management System. CIMS is a comprehensive curation and quality control process that efficiently extracts information from publications.

3. NIH Topic Maps – This website provides a database and web-based interface for searching and discovering the types of research awarded by the NIH. The database uses automated, computer generated categories from a statistical analysis known as topic modeling.

4. SciKnowMine (USC)- We propose to create a framework to support biocuration called SciKnowMine (after ‘Scientific Knowledge Mine’), cyberinfrastructure that supports biocuration through the automated mining of text, images, and other amenable media at the scale of the entire literature.

OpenWetWare– OpenWetWare is an effort to promote the sharing of information, know-how, and wisdom among researchers and groups who are working in biology & biological engineering. Learn more about us. If you would like edit access, would be interested in helping out, or want your lab website hosted on OpenWetWare, pleasejoin us. OpenWetWare is managed by the BioBricks Foundation. They also have a wiki about Science 2.0.

6. LabTrove: a lightweight, web based, laboratory “blog” as a route towards a marked up record of work in a bioscience research laboratory. Authors in PLOS One article, from University of Southampton, report the development of an open, scientific lab notebook using a blogging strategy to share information.

7. OpenScience Project– The OpenScience project is dedicated to writing and releasing free and Open Source scientific software. We are a group of scientists, mathematicians and engineers who want to encourage a collaborative environment in which science can be pursued by anyone who is inspired to discover something new about the natural world.

8. Open Science Grid is a multi-disciplinary partnership to federate local, regional, community and national cyberinfrastructures to meet the needs of research and academic communities at all scales.

9. Some ongoing biomedical knowledge (curation) projects at ISI

IICurate
This project is concerned with developing a curation and documentation system for information integration in collaboration with the II Group at ISI as part of the BIRN.

BioScholar
It’s primary purpose is to provide software for experimental biomedical scientists that would permit a single scientific worker (at the level of a graduate student or postdoctoral worker) to design, construct and manage a shared knowledge repository for a research group derived on a local store of PDF files. This project is funded by NIGMS from 2008-2012 ( RO1-GM083871).

10. Tools useful for scientific content curation

Research Analytic and Curation Tools from University of Queensland

Thomson Reuters information curation services for pharma industry

Microblogs as a way to communicate information about HPV infection among clinicians and patients; use of Chinese microblog SinaWeibo as a communication tool

VIVO for scientific communities– In order to connect this information about research activities across institutions and make it available to others, taking into account smaller players in the research landscape and addressing their need for specific information (for example, by proving non-conventional research objects), the open source software VIVO that provides research information as linked open data (LOD) is used in many countries. So-called VIVO harvesters collect research information that is freely available on the web, and convert the data collected in conformity with LOD standards. The VIVO ontology builds on prevalent LOD namespaces and, depending on the needs of the specialist community concerned, can be expanded.

11. Examples of scientific curation in different areas of Science/Pharma/Biotech/Education

From Science 2.0 to Pharma 3.0 Q&A with Hervé Basset

http://digimind.com/blog/experts/pharma-3-0/

Hervé Basset, specialist librarian in the pharmaceutical industry and owner of the blog “Science Intelligence“, to talk about the inspiration behind his recent book entitled “From Science 2.0 to Pharma 3.0″, published by Chandos Publishing and available on Amazon and how health care companies need a social media strategy to communicate and convince the health-care consumer, not just the practicioner.

Thomson Reuters and NuMedii Launch Ground-Breaking Initiative to Identify Drugs for Repurposing. Companies leverage content, Big Data analytics and expertise to improve success of drug discovery

Content Curation as a Context for Teaching and Learning in Science

#OZeLIVE Feb2014

http://www.youtube.com/watch?v=Ty-ugUA4az0

Creative Commons license

DigCCur: A graduate level program initiated by University of North Carolina to instruct the future digital curators in science and other subjects

Syracuse University offering a program in eScience and digital curation

Curation Tips from TED talks and tech experts

Steven Rosenbaum from Curation Nation

http://www.youtube.com/watch?v=HpncJd1v1k4

Pawan Deshpande form Curata on how content curation communities evolve and what makes a good content curation:

http://www.youtube.com/watch?v=QENhIU9YZyA

How the Internet of Things is Promoting the Curation Effort

Update by Stephen J. Williams, PhD 3/01/19

Up till now, curation efforts like wikis (Wikipedia, Wikimedicine, Wormbase, GenBank, etc.) have been supported by a largely voluntary army of citizens, scientists, and data enthusiasts. I am sure all have seen the requests for donations to help keep Wikipedia and its other related projects up and running. One of the obscure sister projects of Wikipedia, Wikidata, wants to curate and represent all information in such a way in which both machines, computers, and humans can converse in. About an army of 4 million have Wiki entries and maintain these databases.

Enter the Age of the Personal Digital Assistants (Hellooo Alexa!)

In a March 2019 WIRED article “Encyclopedia Automata: Where Alexa Gets Its Information” senior WIRED writer Tom Simonite reports on the need for new types of data structure as well as how curated databases are so important for the new fields of AI as well as enabling personal digital assistants like Alexa or Google Assistant decipher meaning of the user.

As Mr. Simonite noted, many of our libraries of knowledge are encoded in an “ancient technology largely opaque to machines-prose.” Search engines like Google do not have a problem with a question asked in prose as they just have to find relevant links to pages. Yet this is a problem for Google Assistant, for instance, as machines can’t quickly extract meaning from the internet’s mess of “predicates, complements, sentences, and paragraphs. It requires a guide.”

Enter Wikidata. According to founder Denny Vrandecic,

Language depends on knowing a lot of common sense, which computers don’t have access to

A wikidata entry (of which there are about 60 million) codes every concept and item with a numeric code, the QID code number. These codes are integrated with tags (like tags you use on Twitter as handles or tags in WordPress used for Search Engine Optimization) so computers can identify patterns of recognition between these codes.

Now human entry into these databases are critical as we add new facts and in particular meaning to each of these items. Else, machines have problems deciphering our meaning like Apple’s Siri, where they had complained of dumb algorithms to interpret requests.

The knowledge of future machines could be shaped by you and me, not just tech companies and PhDs.

But this effort needs money

Wikimedia’s executive director, Katherine Maher, had prodded and cajoled these megacorporations for tapping the free resources of Wiki’s. In response, Amazon and Facebook had donated millions for the Wikimedia projects. Google recently gave 3.1 million USD$ in donations.