Adding a comment to a PNG or JPG header with Ruby and RMagick

Whenever you create and distribute an image, you should consider putting information in the header, such as the image title and your name and usage restrictions (if any). If you're putting the image into the public domain, you should specify that the image is a public domain image.

These issues are discussed in depth in my web page, Implementing an RDF Schema for Pathology Images.

The header of an image is a text block that is not visible when the image is viewed, but which can easily be stripped from the image.

Here is are two short Ruby scripts. The first script enters a comment into an image header. The second script extracts and displays the comment.

script pdfadd.rb
#!/usr/local/bin/ruby
require 'RMagick'
include Magick
walnut = ImageList.new("neo1.png")
walnut.cur_image[:Comment] = "Developmental Lineage
                            Classification
                            of Neoplasms
                            Copyright (C) 2007
                            by Jules J. Berman
                            and distributed under
                            the GNU Free
                            Documentation License"
walnut_copy = ImageList.new
walnut_copy = walnut.cur_image.copy
walnut_copy.write("out.jpg")
exit


script pdf2.rb
#!/usr/local/bin/ruby
require 'RMagick'
include Magick
walnut = ImageList.new("out.jpg")
walnut.properties{|name, value|
                 print "#{name} #{value}\n"}
exit

This scripts require RMagick, and instructions for acquiring RMagick are available.

The first script, pdfadd.rb, adds a comment to an image and copies the png image to
a jpg image.

The second script, pdf2.rb, extracts and prints the comment from the jpeg image.

The output of the second script is:

C:\ftp>pdf2.rb
Comment Developmental Lineage
                            Classification
                            of Neoplasms
                            Copyright (C) 2007
                            by Jules J. Berman
                            and distributed under
                            the GNU Free
                            Documentation License
JPEG-Colorspace 1
JPEG-Sampling-factors 1x1

The image, neo1.png, is:

---

In June, 2014, my book, entitled Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases was published by Elsevier. The book builds the argument that our best chance of curing the common diseases will come from studying and curing the rare diseases.

I urge you to read more about my book. There's a generous preview of the book at the Google Books site. If you like the book, please request your librarian to purchase a copy of this book for your library or reading room.

- Jules J. Berman, Ph.D., M.D. tags: common disease, orphan disease, orphan drugs, rare disease, disease genetics

Obviousness in Patents

On April 30, 2007, the U.S. Supreme Court, in a unanimous opinion, reversed a decision of the Court of Appeals, and determined that a certain patent claim (read opinion if interested in details) was obvious (and thus not enforceable).

The text of the opinion is available.

As someone who has been following the patents issued on medical standards, and on the uses of medical standards, I have long been interested in the "obviousness" issue. For a device to be patented, it should be new, useful and non-obvious. The problem is that it can be difficult to determine when a device is obvious.

The Supreme court opinion provides a fascinating discussion of the principles of obviousness. I particularly liked the discussion on pages 12-24, which addressed general issues of obviousness.

One issue related to the use of combinations of prior art in a novel manner. This is the most common way in which software gets patented. With virtually no exception, all software is built from algorithms that were already in existence. The novel combination of prior algorithms can produce a new, non-obvious and useful device.

My [layman's] interpretation of the Supreme Court opinion is that merely putting together prior art to make a new device can only qualify for a patent if the resulting device is unexpected, because people in the field would not be expected to put the prior art together in the manner of the patent or because the result of combining the prior art yielded a result that would not have been predicted by the people in the field.

It seems as though the decision raises the bar for patents, particularly patents that are built on prior art (e.g., all software and most software stanndards). I urge all those involved in software standards to read the Supreme Court decision and draw their own conclusions.

Jules Berman

---

Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.

Intro to RDF biomedical specifications

Many of us in the healthcare and life sciences spend a non-significant portion of our professional lives preparing data that will be entered into large databases.

Sometimes databases disappoint us. For a variety of reasons, we can never seem to merge our data with data produced by colleagues who have used a different database. Often, databases within a single institution are incompatible. The solution, we are told, is data standards. If we could mutually decide what data we need to store and how the stored data should be structured, then our databases would be compatible. Our trust in the wisdome of standards has fueled thousands of standards initiatives in the healthcare field.

The problem is that compliance with standards is often very low, and standards themselves can be flawed. As technologies change, standards do not always keep apace. This often results in obsolete standards or standards with multiple versions with idiosyncratic implementations.

RDF (Resource Description Framework) is a formal method for describing specified data objects with paired metadata and data and is prepared in XML syntax. In the next few blogs, I will try to show that RDF-specified data provides some of the functionality of standards. In addition, RDF-specifications greatly expand our ability to understand information. In my opinion, all life science professionals can benefit from understanding the basics of RDF.

-Jules Berman tags: biomedical, data standards, metadata, rdf, specifications

---

Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.

Questions to ask before creating a new standard

As any regular reader of this blog must know, I'm not a big fan of standards development organizations. In most instances where a community would like a standard, they would be better served by a specification.

However, if you're considering a new standards effort, you might want to first answer the following set of questions.

1 Is there a pre-existing standard that covers the same technology?

2 If there is a pre-existing standard, can it be enhanced or modified to provide a desired functionality?

3 How much will it cost to develop the standard?

4 How long will the standards development process take?

5 Will the intended beneficiaries of the standard pay for the standards development process?

6 Who will develop the standard? Are the selected developers competent to produce an adequate standard?

7 Are any of the developers conflicted? Do they stand to profit if the standard is developed in a specific way?

8 Do any of the developers have proprietary software or data that they may wish to include in the standard?

9 Are the expected developers committed to work through the duration of the standards development process, and are they committed to providing all of the time and energy needed to develop the standard?

10 Will there be a mechanism whereby drafts of the standard are reviewed openly by the public? Will the minutes of the working committee be made public? Will public comments be used to modify successive drafts of the standard?

11 Will the standard have dependencies on other standards? If so, are there intellectual property issues that must be resolved before development begins? Will these issues require licenses or royalty agreements from the standards developers or the standards users?

12 Once created, is the standard likely to be adopted? Is the anticipated standard easily implemented?

13 Who will be the adopters of the standard? Are the expected standard adopters included in the development process for the standard?

14 Will the standard benefit a range of users beyond the standards developers?

15 What are the hazards that the standard may produce, and who might be hurt by the standard? In particular, will any entities be disadvantaged if they cannot readily adopt the standard?

16 Is it necessary to have the standard approved by an external organization?

17 If so, who will pay for the extra costs of obtaining approval from an external standards organization?

18 Will the standard need to be continuously updated and modified? Is there a planned process for producing multiple versions of the standard?

19 Is it really important to have the standard? Is it worth the effort?

-Jules Berman, exceprted from Biomedical Informatics

---

My book, Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information was published in 2013 by Morgan Kaufmann.

I urge you to explore my book. Google books has prepared a generous preview of the book contents.

tags: big data, metadata, data preparation, data analytics, data repurposing, datamining, data mining, conflicts, data standards, new standards, sdo, specifications, standards committees

Searching for U.S. patents that encumber a standard

The USPTO (US Patent and Trademark Office) has a website that permits searches of issued patents (database extends to 1790). A separate search engine finds patent applications currently under review by the USPTO.

If you are developing a standard and you wish to avoid including patented technology in the methods included in your standard,

or

if you have developed a standard and are interested in protecting your users against trivial or non-innovative patents attached to the uses of your standard,

or

if you are a standards user and wish to avoid using standards that are encumbered by patents,

or

if you are a standards user who has chosen a standard and wish to avoid infringement on a patent that encumbers the standard,

you will want to visit the USPTO patent search site.


Here is the web page at http://appft1.uspto.gov/netahtml/PTO/search-adv.html for a search of pending applications with the word "DICOM" in the title of the application.



Here is the returned web page:



In the next blog, I will use DICOM (Digital Imaging and Communications in Medicine) as an example of a standard for which a user can conduct USPTO patent searches.

- Jules Berman

---

My book, Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information was published in 2013 by Morgan Kaufmann.

I urge you to explore my book. Google books has prepared a generous preview of the book contents. If you like the book, please request your librarian to purchase a copy of this book for your library or reading room.

tags: big data, metadata, data preparation, data analytics, data repurposing, datamining, data mining, coercive standards, data standards, DICOM, embedded patents, intellectual property, patent search, sdo, specifications, standards development organizations, uspto

Data standards should not be coercive

In a prior post, I wrote about monopolistic standards: "Yet somehow, when a committee gets together to write a data standard, they often develop a very self-centered culture that tries to eliminate the 'competing' standards."

Standards committees sometimes display group behavior that can be described as antisocial or even sociopathic. They often want their standard to be the only standard used in a data domain (self-centered behavior). If there are other standards in the data domain, they sometimes use coercive methods (bullying) to force everyone to use their standard. They might also actively enlist organizations to enforce the standard on their members.

The most common coercive argument involves telling people that everyone else is using the standard, and if they don't use the standard, they'll lose business or they will be ostracized or ignored by the user community. Coercive behavior should not be tolerated in the user community.

I've personally seen coercive behavior in colleagues who are very decent people who would never dream of bullying another person. Somehow, when sociopathic behavior is developed through a committee process, people lose sense of what they are really doing. To my way of thinking, this is just another reason to favor specifications over standards, when feasible.

-Jules Berman

---

My book, Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information was published in 2013 by Morgan Kaufmann.

I urge you to explore my book. Google books has prepared a generous preview of the book contents.

tags: big data, metadata, data preparation, data analytics, data repurposing, datamining, data mining, coercive standards, data standards, specifications, standards development organizations

Data standards should not be monopolistic

In a prior blog, I listed 16 good practice suggestions for SDOs (Standards Development Organizations).

One suggestion was:

"Make optional standards, not required standards, so that the user community is not locked into one implementation."

This suggestion seems to defy common sense. The purpose of a standard is to provide a common process for a user community. Wouldn't a standard lose its significance if it were designed to be one of many?

First off, remember that I'm only addressing data standards (not physical standards). Data standards are special because, in many cases, you can interconvert data from one standard to another quite easily. Data standards are usually developed to facilitate data exchange and interoperability in a defined data domain. It is seldom the case that a given data standard will have universal appeal. We have dozens (if not hundreds) of image format standards. The multiplicity of standards can be useful. There are times when a GIF format is superior to a JPEG and other times when a PNG format is appropriate. Most people who work with images have robust file conversion applications that make it easy to exchange many different image formats.

Yet somehow, when a committee gets together to write a data standard, they often develop a very self-centered culture that tries to eliminate the "competing" standards.

If a data domain has one standard, then patents that encumber the uses of the standard will impact negatively on everyone. If a data domain has multiple standards, then the user community can simply switch between available standards to avoid patent prosecution. They might use one standard to accomplish a task that is exempt from patent infringement (typically the task for which the standard was designed and for which no patents apply). If/when a newly patented use of the one standard emerges, the user can avoid legal headaches by switching to another data standard not covered by the patent. It's really quite simple.

Members of data standards committees should understand that the purpose of any standards effort is to serve the user community with improved methods for exchanging data, for software interoperability and for enhanced opportunities to use data. A data standard is just an arbitrary document. It hardly even rates as a "thing" since it has no physical existence. SDOs should try to make new standards that fill a particular utility "niche" not covered by other standards in the same domain. If users gravitate to the standard in preference to other standards, that's OK. But crushing the "competition" should not be a goal for any SDO.

-Jules Berman

---

My book, Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information was published in 2013 by Morgan Kaufmann.

I urge you to explore my book. Google books has prepared a generous preview of the book contents. If you like the book, please request your librarian to purchase a copy of this book for your library or reading room.

tags: big data, metadata, data preparation, data analytics, data repurposing, datamining, data mining

Why governments rarely create data standards

As someone who has been involved in a variety of standards initiatives, I'm amused when the suggestion is raised that the federal government create the standard. The reasoning often goes something like this: "If the federal government produced the standard, the costs of developing and maintaining the standard would be absorbed by taxpayers, and the standard would be legitimized and maybe even required by government regulation."

Well it doesn't work like that. Aside from the show-stopping law that severely limits the U.S. government from creating data standards, there are practical reasons for the government to demure.

First, most data standards fail. They are either never finished, or they are immediately ignored by the intended user community, or they are replaced by competing standards that cover the same data domain, or they eventually become so obsolete that they are abandoned. There's very little reason for the government to become embroiled in efforts that typically fail.

Second, standards often impose significant implementation costs on the user community. As discussed in earlier blogs, standards can be encumbered by intellectual property, requiring users to pay license fees or patent royalties for the uses of the standard. Also, the standard may benefit some users and hurt others. If a standard benefits the members of the committee that created the standard at the expense of members of the user community who were excluded from the standards development process, lawsuits from allegedly injured users may result. SDOs are aware that, unless their standards are created fairly, the SDO (and its entity members) may be vulnerable to prosecution under the RICO Act.

Why would the government want to get involved in this kind of mess?

As discussed in a prior blog, there are instances when the functionality of standards can be achieved with specifications. The flexibility and freedom of specifications reduces many of the problems inherent in standards. Methods for developing specifications as an alternate to standards, have been described in a draft white paper and will be will be the subject of future blogs.

-Jules Berman

---

Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.

Protecting the basic uses of a Standard

Yesterday's post took an example from DICOM to describe how the uses of an existing standard can be patented. A standard, even if it is a free and open standard, has little value if the intended uses of the standard are encumbered by patents. This would mean, in effect, that the user community must license the standard for uses that are covered by patents (or risk infringeing on one or more patents).

What can SDOs (Standards Development Organizations) do to prevent this problem? I am not a lawyer, and cannot give legal advice, but I would suggest that the following approach is sensible:

When the standard is being developed, the SDO should think about all the intended uses for the standard and publish a document (as an SDO white paper or as a journal publication) that describes, in detail, the ways that the standard can be used, supplying source code, instructions, sample implementations, user commentary, citations to relevant publications in the field, etc. This would help create prior art for the described uses of the patent. When the SDO provides public documentation for the common, expected uses of the standard, it would make it difficult for someone to come along and claim the those methods in a patent.

Also, SDOs should be prepared to work with their Patent Office to explain how patent applications related to their standard may be preceded by scientific art or may provide no new or non-obvious functionality to the standard. As described in an earlier post, the USPTO recognizes that software patents are a difficult area and has a program to seek guidance from the software community.

Suppose an inventor conceives of a totally new use of an existing standard and develops a patentable process or application for this new use. How would an SDO defend the standard in this case. Well, there might not be any defense. After all, if someone really comes up with a novel use for a standard that has a real-world application, why shouldn't their intellectual property be covered by a patent? The problem for SDOs comes from patents that cover customary, expected uses of a patent. SDOs with nothing in place to protect the basic uses of the standard have not done their job very well.

-Jules Berman

---

My book, Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information was published in 2013 by Morgan Kaufmann.

I urge you to explore my book. Google books has prepared a generous preview of the book contents. If you like the book, please request your librarian to purchase a copy of this book for your library or reading room.

tags: big data, metadata, data preparation, data analytics, data repurposing, datamining, data mining

The uses of free standards can be patented

In a prior post, I described several ways in which data standards can become encumbered with intellectual property. One of these involves patenting the way that a standard is used. Even when a patent is free, there is nothing to stop an inventor from patenting uses for the standard.

DICOM (Digital Imaging and Communications in Medicine) exemplifies a standard that has a patented use. DICOM is a widely used image standard for radiologic images. Currently, there is an effort to have all medical specialties adopt DICOM as the exclusive format for all medical images.

U.S. Patent 6725231 , issued Apr 20, 2004, to Jingkun Hu and Kwok Pun Lee and assigned to Koninklijke Philips Electronics N.V., has the following claim.

"1. A method for mapping a DICOM specification into an XML document, comprising: mapping each entry of a DICOM table of the DICOM specification into a corresponding XML element of a plurality of XML elements,outputting each XML element of the plurality of XML elements to the XML document, in an output format that conforms to at least one of: an XML document-type-definition and an XML Schema."

A similar patent by the same parties sits at the European Patent Office (EPO).

Informaticians will note that teasing the data elements from a data object and porting them into XML is the bread-and-butter of modern informatics. A patent claim that covers this basic use of DICOM may be highly problematic.

SDOs(Standards Development Organizations) cannot stop inventors from patenting new and useful applications of their standards. However, there are easy ways for SDOs to reduce the risk of inventors patenting the common, expected uses of their standards. These will be described in a future post.

-Jules Berman tags: biomedical informatics, converting to xml, data standards, DICOM, embedded patents, european patent office, medical images, patent claims, radiology images, sdo, uspto, xml, science

---

Science is not a collection of facts. Science is what facts teach us; what we can learn about our universe, and ourselves, by deductive thinking. From observations of the night sky, made without the aid of telescopes, we can deduce that the universe is expanding, that the universe is not infinitely old, and why black holes exist. Without resorting to experimentation or mathematical analysis, we can deduce that gravity is a curvature in space-time, that the particles that compose light have no mass, that there is a theoretical limit to the number of different elements in the universe, and that the earth is billions of years old. Likewise, simple observations on animals tell us much about the migration of continents, the evolutionary relationships among classes of animals, why the nuclei of cells contain our genetic material, why certain animals are long-lived, why the gestation period of humans is 9 months, and why some diseases are rare and other diseases are common. In “Armchair Science”, the reader is confronted with 129 scientific mysteries, in cosmology, particle physics, chemistry, biology, and medicine. Beginning with simple observations, step-by-step analyses guide the reader toward solutions that are sometimes startling, and always entertaining. “Armchair Science” is written for general readers who are curious about science, and who want to sharpen their deductive skills.