by Ton Sluiter, Product Manager, Textkernel
Every day more than a million new vacancies from thousands of different websites in 10 different countries are added to Jobfeed. These vacancies are parsed into more than 50 variables such as job title, location, organization, contract type, job description, employer description etc.
This information is further enriched due to the use of Textkernel’s AI models with more than 30 variables such as normalized profession, type of industry, organization size, normalized skills, region etc.
All this information is available in Jobfeed, and through the portal interface, users can easily analyze key market trends. However, as a portal user, your ability to do detailed research is limited because much of the data is aggregated for ease of use.
This is where the Jobfeed API comes in
By using Jobfeed’s API you can tap into an infinite source of data with all enriched individual vacancies and job postings. A true “candy store” for every business analyst or data scientist in the staffing industry, or labor market researchers at government agencies, research institutes or universities.
In my previous job at USG People, the second largest staffing agency in the Netherlands, we have been using Jobfeed’s API for several studies. Here are a few examples.
Sales and Account Management wanted to have an overview of the accounts of the main competitors. And, as more and more staffing agencies publish the name of their clients in the vacancies, this information is also available in Jobfeed.
By extracting the data from the Jobfeed API we could analyze our position per account compared, as well as per function against our competitors. Account Management used this information in meet-ups with clients, and the insights were also helpful in the tender process at prospects.
Terms of employment
As part of a project to improve the content of vacancies we wanted to research the development of some typical conditions and benefits like education/upskilling offers and pension schemes. In the Jobfeed API the full text of a vacancy is available as well as sections like the job description and the conditions and benefits of a job. Thus we were able to extract this information combined with profession, publication date, organization, industry and more to do deeper analysis.
With all this data we were able to study the evolution over time of specific conditions and benefits. The insights provided us with very useful information on what to put in a specific vacancy to attract applicants.
Labor market insights
Customers asked our consultants to give them insights into the local labor market conditions. By combining internal data such as applications per vacancy, number of placements and salary levels, external data from available sources on outflow from education, unemployment per occupations, and data from the Jobfeed API on development of vacancies, we were able to create an internal dashboard that easily surfaced insights on the difficulty to attract applicants per function.
When we look at our internal data we see labor market development mixed with the choices that our organization made. To perform a benchmark and add contextual information you require data that looks further. Jobfeed does exactly that and the API enables the combination of both the internal and external view. An interesting base for data analysts to explore further.
– Riecold Veldkamp, Lead Solution Engineer IT Strategy & Digital Office, USG People
Matching on external vacancies for lead generation
As in many staffing agencies, USG People receives more applicants than can be placed. Most of these applicants have very useful skills and educations, and because they applied we could suggest other jobs that matched their candidate profile. In the Applicant Tracking System (ATS) we were able to match high quality applicants to external vacancies of direct employers that were still open after much time, indicating the role was difficult to fill and that the prospect would likely be interested in your matching candidates.
Because the Jobfeed API also provides the contact details such as the name, phone number and email address it is easy to reach out and present a perfect match. A win-win-win for the applicant, employer and staffing agency.
For us, the Jobfeed API was a holistic tool that delivered value in many different areas. From providing labor market insight that allowed our consultant to deliver strategic value to customers, through to lead generation that allowed us to place more of our sourced candidates.
For further information on how the Jobfeed API can deliver value for your business you can get in touch with our sales team.
The new Jobfeed experience is live through a public beta for our customers! While still under development, customers with access can try out the new layout and design as a preview of upcoming developments. To access the new UI, simply log into Jobfeed as normal and select “Try the new Jobfeed” in the upper left corner of the portal.
You can return to the old, familiar design at any time. The Jobfeed team will continue adding more functionality in the coming months, constantly bearing your valuable feedback in mind. Once complete, the the new design will become the default portal interface.
We’d love to hear from you
There is a feedback button to the right of your screen where you will be presented with a short survey. Please let us know how you experience the new design!
We’ve made many improvements to the design and usability, but rather than detailing them here we’d encourage you to log into the portal and try them out! Not a Jobfeed customer yet? Get in touch and our sales team will arrange a personalized demo.
Can I use Jobfeed in my usual language?
This preview is only available in English for now. All other languages will be made available before the new design will become the default.
Amsterdam/San Diego, January 07, 2021 – Textkernel, specialists in machine intelligence for matching people and jobs, and Tracker, a leading provider of cloud-based Recruitment, Applicant Tracking and CRM software, announce a new partnership allowing Tracker clients to place more of their sourced candidates and optimize the staffing cycle.
AI-Powered Parsing and Matching available in Tracker
Available now in Tracker, Textkernel’s high accuracy Resume and Job parsing creates the structured candidate and job records. This allows recruitment agencies to understand the talent in their database, and forms the foundation of effective and relevant matches between candidates and jobs.
Meanwhile, Textkernel’s Match technology allows recruiters to quickly match their candidates against potential future roles in Jobfeed, the largest searchable job database for lead generation, saving recruiters time and maximizing their efforts to win more business.
“The partnership between Textkernel and Tracker is an exciting opportunity to bring our AI-powered parsing and matching technology along with our Jobfeed Big Data tool to even more staffing and recruiting professionals across the globe. In this high-pressure industry speed and maximizing effort is essential, and we have no doubt Tracker clients will find value in our AI-powered matching and Jobfeed database.” – Philip Van Leeuwen, Director of Global Partnerships, Textkernel
“With 12 years of experience helping staffing and recruiting firms build better relationships, processes, and revenue, Tracker is continually on the lookout for partners that will complement our recruitment software with best-in-class integrations and technology solutions. We’ve recently chosen to partner with Textkernel for their integrated resume and structured data parsing. Textkernel’s Extract! provides our customers with the highest-quality multilingual parsing solution currently on the market.
We have also made the exciting decision to integrate with Textkernel’s labor market intelligence, as Textkernel offers superior vacancy coverage to ensure that our customers do not miss any potential postings. From our customers, we know that this is key for both business development purposes, but also for local market intelligence purposes.” – Andy Jones, co-founder, Tracker
To learn more about the benefits of this integration, contact us.
Amsterdam/London, December, 09, 2020 – Textkernel, specialists in machine intelligence for matching people and jobs, and CloudCall, experts in making business communications easier, quicker and more powerful, announce a new partnership allowing staffing professionals to save time by finding and connecting with top talent quicker than ever before in Bullhorn.
Empower recruiter workflows with intelligent automation to save time and connect people and jobs
Textkernel’s advanced semantic search, sourcing and matching technology, integrated directly in Bullhorn allows staffing professionals to create a match based on either a job description or resume with a single click, identifying and shortlisting top candidates from your Bullhorn database or external sources. Once you’ve created your shortlist, candidates can be easily sent to Cloudcall through Bullhorn’s tearsheet functionality to help connect more efficiently. This can be done either through CloudCall’s PowerDialier, which automates phone outreach to clients and updates Bullhorn records once connected; or through Broadcast SMS, which sends a personalized message with important details to all candidates in the tearsheet.
“Whatever the market conditions, recruiters know that finding and connecting with top talent faster than the competition is key to winning business and keeping both candidates and clients happy. This partnership between Textkernel and CloudCall, seamlessly integrated into Bullhorn, offers another way recruiters can save time through automated workflows, allowing them to focus more effort on the human side of recruiting.” – Philip Van Leeuwen, Director of Global Partnerships, Textkernel
“Textkernel and CloudCall solutions already provide a huge number of benefits to our customers. By using both technologies together, Bullhorn are continually empowered to work more efficiently and productively, with enhanced capabilities. We are delighted to work alongside the excellent team at TextKernel.” Daniel Fox, Channel Marketing Director at CloudCall
To learn more about the benefits of this seamless integration, contact us.
Amsterdam/San Francisco, December, 3, 2020 – Textkernel, specialists in machine intelligence for matching people and jobs, and Mya Systems, experts in automating candidate engagement and communications at scale, announce a new partnership allowing staffing professionals to find top talent and recruit faster using cutting-edge AI technology.
Save recruiters time by finding the best talent fast and instantly engaging and converting the most qualified leads
Textkernel’s advanced semantic search, sourcing and matching technology, integrated directly in Bullhorn, allows staffing professionals to create a match based on either a job description or resume with a single click, identifying and shortlisting top candidates from your Bullhorn database or external sources. Once you’ve identified your talent, they can be seamlessly added to a Mya Outreach campaign. Here Mya’s intelligent conversational AI automates candidate outreach and engages directly with candidates to screen and schedule interviews at a convenient time and location – saving recruiters valuable time and ensuring an unparalleled recruiter and candidate experience.
“We’re really excited by the value our new partnership with Mya will deliver to Bullhorn clients. Both companies understand how intelligent automation can save recruiters significant time and enhance their workflow for speed and scale. By allowing technology to handle the more administrative elements of their job, recruiters will have more time to focus on the areas where a human touch is vital.” – Philip Van Leeuwen, Director of Global Partnerships, Textkernel
“The integration between Mya and Textkernel marks an exciting opportunity to deliver even more value to Bullhorn customers. Combining the power of Textkernel’s powerful candidate search and match capabilities with Mya’s groundbreaking conversational AI to automate candidate outreach at scale, both seamlessly integrated into the Bullhorn platform, will deliver significant efficiencies for our staffing clients. Through this exciting new partnership, this game-changing, fully integrated solution offers our Bullhorn customers a truly automated recruitment experience.” – Mike Pauletich, VP of Global Alliances & Partnerships, Mya Systems
To learn more about the benefits of this seamless integration, contact us.
- Location: Online
- Date: 5 November 2020
Embracing online events – Textkernel Platinum sponsor at EngageX Europe!
With the 2020 events calendar turned on its head, Bullhorn EngageX Europe promises to bring you everything you love about the Engage series of staffing conferences in an immersive online format.
Here’s what you can look forward to:
- Our CEO, Gerard Mulder, will host a roundtable on how Understanding supply and demand of Skills is the next big opportunity for Staffing.
- You’ll hear a testimonial from one of our happy customers during the Marketplace showdown
- And of course, our team will be available to meet and discuss today’s challenging times in staffing or answer any questions you might have.
So whether you’re looking to improve your workflow and boost recruiter efficiency, struggling to find business opportunities in today’s economic downturn, or having trouble placing all your candidates our AI-powered solutions can help your business not just survive 2020, but thrive!
Discover the full Textkernel offering in Bullhorn, or learn more about our partnerships with out marketplace partners:
Amsterdam, September 29th, 2020
Textkernel announces a change in the ownership of the company, as CareerBuilder sells its ownership in the company to the Dutch investment firm, Main Capital Partners. CareerBuilder and Textkernel will continue to work together, and have agreed upon a longer term partnership plan and license agreement.
Main Capital Partners is a strategic investor in the software industry based in The Netherlands. With a strong focus on accelerating growth and generating business value in a diverse network of SaaS organizations across the Benelux, DACH and the Nordics, Main Capital Partners is an ideal partner to support Textkernel’s future growth strategy.
Over the course of its 20-year history, Textkernel has focused its efforts on building best-in-class document parsing as well as semantic search and match product offerings. By developing technology that returns highly accurate results, Textkernel has gained a strong competitive position within its market.
Textkernel has a significant customer base of the world’s largest staffing and recruitment firms that put Textkernel’s AI at the core of their operational processes to increase efficiencies that deliver customer and shareholder value.
In recent years, Textkernel’s offering has become more interesting and relevant for the Corporate HR market that is looking to create business value by better operationalizing their talent acquisition, as well as enabling competitive advantage through better insights for talent management practices.
Collaboration Textkernel and Main
- Current management team Gerard Mulder (CEO) and Guus Meijer (COO) will stay onboard and will remain shareholders of Textkernel.
- Together, Textkernel and Main will focus on autonomous growth and further development of the technology platform required to execute on its ambitious growth plans in the coming period.
- In addition, the combination will pursue a selective strategy for smart acquisitions in the broader HR software space.
Gerard Mulder, CEO at Textkernel: “We are delighted to have the support of Main Capital Partners to drive our ambitious expansion plans for the future. Despite the challenging economic context, we see ample runway for growth across diverse customer segments and geographies. Having Main Capital as a strategic investment partner allows us to benefit from their deep expertise and diverse SaaS network. We look forward to delivering on our vision as an AI provider for business leaders seeking innovative solutions to solve their most pressing talent acquisition and management challenges.”
Pieter van Bodegraven, Partner at Main Capital Partners: “Strong potential is visible in this particular part of the HR software market. We have known the management team of Textkernel for many years and are pleased with the opportunity to collaborate. We are impressed by the fact that the company is able to realize autonomous growth in a profitable way, while expanding internationally at the same time.”
Textkernel works with over 1,000 HR and staffing organizations worldwide to bring the latest in artificial intelligence technology to our customers’ fingertips. We work with large, global companies across multiple industries to deliver multilingual parsing, semantic search and match, and labor market intelligence solutions.
About Main Capital Partners
Main Capital is a strategic investor with an exclusive focus on the software sector in the Benelux, DACH and Nordics. Main has a long term horizon around successful partnerships with management teams, with the aim of building larger software groups together. Main has approximately € 1 billion in assets under management for investments in mature and growing software companies.
Main Capital’s current portfolio includes fast-growing software and SaaS software companies such as Exxellence, WoodWing, Alfa, Optimizers, Assessio, GBTEC, Onventis, HYPE Innovation, cleversoft, Enovation, SDB Group, Jobrouter, GOconnectIT, Inergy, KING Software, Artegic, OBI4wan, b+m Informatik, ChainPoint, Sofon and RVC. Successful former companies that have grown significantly under Main’s leadership: Connexys (HR software), Roxit (government software), Axxerion (facility management software), Ymor (APM software), Onguard (credit management software) and TPSC (healthcare GRC software).
For more information, please contact:
Charly Zwemstra (Managing Partner)
Main Capital Partners B.V., Paleisstraat 6, 2514 JA, Den Haag
Tel: +31 (0) 70 324 3433 / +31 (0) 6 5127 7805
Gerard Mulder (CEO)
Nieuwendammerkade 26A-5, 1022 AB Amsterdam
Tel: +31 (0) 20 494 2496
Transferable skills in a disrupted job market: a data perspective
By Kasper Kok, Product Owner of Knowledge Resources and Juliette Conrath, Team Lead of Proserv – Southern Europe
The global outbreak of Covid-19 has severely shaken up the job market, both in terms of demand and supply. Millions of professionals in tourism, hospitality and other areas are currently unable to perform their jobs and the possibility of an economic downturn has made organizations cautious to spend and hire. The recent changes in consumer behavior induced by the crisis also have a flip side, however: jobs in delivery services and telecommunications are trending and there is obviously unprecedented demand for medical personnel and volunteers.
A disbalanced market disruption calls for mobility: in a time where entire industries are paralyzed by governmental restrictions, many people are left with no choice but to deviate from their current career path. But where does someone go who has been working in the tourism, entertainment, or hospitality industry all their life? Wouldn’t any employer outside these industries reject them at first glance of their resume, based on a lack of relevant experience?
Here’s some good news: modern staffing and recruitment experts are increasingly interested in tools that can help them identify transferable skills. Job titles can vary from industry to industry and even from organization to organization, so organizations are focused on identifying skill sets and looking at how to transplant skills gained from one experience into the next.
When looking at jobs in terms of the competences that are required to execute them successfully, the opportunities for mobility inside and across professional domains are vast, and opportunities go beyond the obvious. In this article, we’ll provide a data-based perspective on transferable skills across domains. The analyses we present build on three assets that Textkernel has developed over the last two decades: a substantial collection of over 1 billion vacancies, high-quality document parsers that can transform these documents into structured data, and taxonomies of professions and skills according to which vacancies can be classified.
Crawlers, parsers and taxonomies: a recipe for reliable analytics
A first step toward reliable analysis of skills in the job market is access to a large set of job market data. Textkernel web crawlers spider the web for vacancies from a large collection of job boards and staffing portals, totalling tens of thousands of websites. These vacancies are then transformed into structured data using Textkernel’s parsers, which decompose the documents into individual bits of information: job descriptions, candidate requirements, benefits, skills, etc. The final step is to normalize this information. That is, to relate the words found in the texts to the units that are of interest to HR and TA professionals, such as skills and professions and education levels. Normalization, in other words, is about recognizing synonyms that refer to the same concept to ensure that the analysis will be robust to linguistic variation.
Normalization happens based on Textkernel’s various taxonomies. Our Skills Taxonomy contains over 11,000 skills and recognizes over 135,000 synonyms in 6 languages.
In addition to the skill taxonomy, Textkernel maintains a profession taxonomy, which contains 4200 professions. The analyses presented below are based on the millions of jobs in the UK job market, which are normalized according to these taxonomies.
Case studies: the booking agent and the warehouse worker
To show how a large database of parsed and normalized documents can help identify potential professional transitions, we look at two case studies.
Jane is a booking agent, responsible for booking hotels and other travel arrangements. But the office hasn’t seen any orders coming for many weeks now and will be forced to let go of most of their employees.
Jake is responsible for receiving and processing incoming stock in a commercial warehouse, but the warehouse has seen a drastic reduction in business and he is not optimistic that his temporary contract will get extended.
The current crisis has made both Jane and Jake wonder about the next steps in their career. Different from a normal job-transition, the overall decline of travel and retail activities impedes job transition within the same role of even professional domain. But what are their chances in a different role or even another industry, and which of their competences can be transferred to another type of job?
Frequent versus job-specific skills
First, let’s explore the core competencies we can assume Jane and Jake to have. Based on our enriched vacancy database, we can answer a simple question: what skills are most often asked for in job postings for booking agents and warehouse workers?
Skills most frequently found in vacancy postings
|Booking agent||Warehouse assistant|
|1||Customer Service||1||Stock Control|
|3||Sales||3||Packaging and Processing Duties|
|4||Attention To Detail||4||Unloading|
|7||Team-working||7||Hardworking And Dedicated|
|8||Telephone Skills||8||Logistics Operations|
Upon inspection of these skills, you’re likely to notice that some of them are rather generic. Skills like communication and passionate are very frequently required in these professions, but they are not specific to these professions. This ubiquitous demand makes them important skills to develop, but they are unlikely to be among the key reasons for a hire. Rather than looking at the frequency of skills in requisitions for different jobs, we therefore need a measure of how strongly skills are associated with certain jobs. Instead of raw frequencies, we’ll therefore use a metric which we will call job-skill association strength. It has a high value for skills that are in high demand for a given job but not for many other jobs. Going back to our case studies, the following lists show which skills are most strongly associated with booking agents and warehouse assistants.
Skills most strongly associated with the target professions
|Booking agent||Warehouse assistant|
|2||Property Management Systems||2||Forklift Trucks|
|3||Upselling||3||Handling and Load Carrying|
|7||Hotel Reception Duties||7||Packaging and Processing Duties|
|8||Amadeus CRS||8||Warehouse Management Systems|
|9||Front Office||9||Manual Handling|
|10||Attentive Service||10||Logistics Operations|
The next best job: skill-based job transitions
Now that we have a way to characterize jobs in terms of which skills are most strongly associated with them, we can measure the distance between jobs based on overlapping skills. Here are the top 10 closest jobs to those held by Jane and Jake.
Jobs closest to the target professions, based on overlapping skills
|Booking agent||Warehouse assistant|
|1||Head of Reservations||1||Order Picker|
|2||Front Office Manager||2||Warehouse Administrator|
|3||Receptionist||3||Forklift Truck Driver|
|4||Hotel Receptionist||4||Delivery Driver|
|5||Travel Agent||5||Stock Clerk|
|6||Travel Consultant||6||Reach Truck Driver|
|7||Night Porter||7||Truck Driver’s Assistant|
|9||Account Manager Telesales||9||Warehouse Associate|
|10||Head of Reception||10||Packer|
Visualizing the overlap between professions
To get a better grip on the overlap between our protagonists’ profiles and the jobs listed here, we can plot the skill-job associations for two professions against each other. In the charts below, we take the union of the 10 skills that are most strongly associated with each profession and plot their association strengths on the two axes of the chart. The upper-right corner of these plots then represent the set of skills that are associated with both professions. The top-left and bottom-right show those that are associated more with one of the professions than with the other. To aid the interpretation, we plot ellipses around the relevant parts of the axes of the plots, simulating a Venn diagram.
Let’s first have a look at a possible job transition for Jake. From the above list of closest jobs, we can see that many of the possible job options are warehouse-related and therefore perhaps not the most promising options. There’s one job in the list for which there surely won’t be a lack of demand in a time where many people are homebound: delivery driver. Let’s have a look at which skills a warehouse assistant and delivery driver have in common.
This chart suggests that both professions are associated with various skills related to logistics, loading and unloading, and packaging. Jake won’t need his knowledge of Warehouse Management Systems anymore after the job switch, but he will need to learn a few things about defensive driving and tail lift trucks. All in all, these analyses suggest that there’s not much in Jake’s way of transitioning to a role as a delivery driver.
Next, let’s look at the options for Jane. Here too we see that a lot of the most similar professions are within the same domain, or at least have to do with travel in some way. Assuming that hiring in the travel industry will be low in the considerable future, let’s look at a travel-unrelated option: Account Manager Telesales. Here we see how the typical skills of a booking agent overlap with those found in requisitions for telesales roles.
According to this data, both booking agents and account managers in telesales are acquainted with call centers, sales techniques and call reception management. Some further training in b2b principles and sales concepts might be required for her to make a job switch, but there seems to be a solid common ground between the two positions.
But maybe Jane doesn’t like the sales part of her work all that much? Maybe she aspires to a more radical career switch, and hopes that she can contribute to healthcare? Using Textkernel’s profession taxonomy we could restrict the search for job transitions to the domain of healthcare. Based on skill-overlap, our data suggests that the closest medical job to Jane’s current profile is that of Patient Care Coordinator. Let’s look at what these two professions have in common:
Some upskilling will certainly be required for Jane, but judging from this analysis, there are several competences and activities that intersect the professions of booking agent and patient care coordinator. The ones that are more unique to the latter, shown in the top-left section of the plot, can be seen as areas where Jane will need to look for targeted training if she is to take this job transition seriously.
Skill analytics beyond the crisis
Analyses akin to the ones presented here can have implications to mobility questions of any kind, not just those that arise in times of a pandemic. Challenges regarding internal mobility, outplacement, targeted upskilling and strategic workforce planning all benefit from a clear understanding of which skills are shared between different types of jobs. For instance, one might employ skill-overlap analysis to answer questions like “what skills represent the difference between an account manager and a commercial director?” or “what training would help a Java developer become a data scientist?” The charts shown in the appendix can help to answer these questions.
Not having access to the tooling required for skill-oriented profiling, recruiters and employers are often fixated on role descriptions and assume that different roles within or across industries don’t have enough in common to consider out-of-the-box hires. A good understanding of transversal skills is pivotal to a more agile approach to mobility challenges. Using the powerful combination of crawlers, parsers and taxonomies, new opportunities for job transitions or upskilling can be identified that are fruitful in any state of the job market.
Appendix: additional analyses
The below serve as additional example to show areas where skills overlap could benefit areas such as succession planning and workforce mobility:
The impact of Coronavirus (COVID-19) on the US job market is unprecedented. Textkernel and CareerBuilder have teamed up to share labor market insight into how Coronavirus impacts job inventory, top jobs currently available, top hiring employers and more.
Below is a selection of insights, for the latest information be sure to follow #CareerBuilderCovidData on LinkedIn.
Overall job inventory is down, but these employers are leading the way in staffing up to meet demand in industries like Logistics, Insurance, Food Retail and Healthcare.
There are employment opportunities available for a range of skill sets. 5 of the top 20 jobs available now are in the healthcare industry, 5 relate to sales and customer service, 4 require driving and delivery of goods.
Job inventory is down across all industries. Information Technology, Retail Trade and Wholesale Trade are showing the least amount of disruption.
The demand for all healthcare-related workers is up – but, critical care positions are more than 2x in need as COVID cases exponentially rise in the US.
We’ve seen certain pockets of demand in the Transportation & Warehousing industry, but as a whole it’s down 45% from the 3-year average.
Mississippi, Kentucky and West Virginia are seeing the biggest dips in job postings by state.
Jobfeed data powers analytics dashboards across Europe and North America, including:
- Emsi (US & Canada) – Job posting analytics dashboard – Track job posting trends by day, week, and month and compare to 2019 averages. You can also filter by region, industry, company, job, and skill.
Textkernel takes great pride in our strong ties to the academic community, particularly since we started from humble beginnings in 2001 as a private, commercial R&D spin-off with a focus on research into Natural Language Processing and Machine Learning at the Universities of Tilburg, Antwerp and Amsterdam.
And so with great excitement, our Head of Ontology, Panos Alexopoulos, has announced the release of his book: “Semantic Modeling for Data – Avoiding Pitfalls and Breaking Dilemmas”. Published by O’Reilly, the book serves as a practical and pragmatic field guide for data practitioners that want to learn how semantic data modeling is applied in the real world.
The book is available for purchase global from all good online and physical book retailers. For a complete list of where to buy, visit Panos’ site.
We sat down with Panos to discuss a bit about how the concept of the book came about, and what readers can expect:
Avoiding Pitfalls and Breaking Dilemmas
“The book is about the broader topic of Semantic Data Modeling which is actually the task and problem of creating representations and structures of data in a way that the meaning of the data is explicit and commonly shared and understood by both systems and humans,” Panos explains.
“That’s a general challenge that information technology has, and especially now with AI technology in place, it’s important that meaning is understood in an explicit way by humans and machines. The book fills a gap in the literature and the market, especially when it comes to book about practitioners and professionals. There are several academic books describing how to build an ontology, what is the underlying theory behind data semantics etcetera, but the problem is usually this information is sparse, all around the place, either in papers or in presentations, so it’s never gathered together. What is lacking is the industry perspective, the perspective from the side of a practitioner – what it means to build, use and maintain these kinds of models in the real world, in organizations in the industry. My work here at Textkernel has been one of the key inspirations of the book, so many of the things I’ve seen here both positive and negative have contributed to me being a better modeler and professional, and I wanted to share these experiences with the rest of the community. That’s how the book was born.”
The role of early feedback
“It’s always important when you write a book to get early feedback, and what O’Reiley, my publisher, allows you to do is provide the book online, provide some raw and unedited content on he platform so that any users can see the book and are able to share their opinion, give their feedback, find mistakes, find things that may be wrong or may want more information. That’s extremely useful feedback because in the end it’s all about removing ambiguity. And because this book is not addressed to only one community, it’s actually a wider community and there are different sub-communities in the data world that don’t necessarily use the same terminology or necessarily have the same experiences it’s important that all these sub communities have a an opportunity to say something about the book.”
“Semantic Modeling for Data” is expected to be published in November, and is currently available as an early release version.