Devonthink vs Devon note...what's the difference

Can I think of Devon note as a more bare bones version of devon think, like DT personal is more bare bones than DT pro? Or is Devon note a distinct product?

I have had DT personal for a little while now. I have used it…a bit, but I admit, it’s not leaping alive on the dock very often. I can’t quite get into the swing of making regular use of it. Partly due to format inconsistencies, it’s ability to deal with an MS word docoment for example is limited, and I find the text formatting interface a bit clunky…but I do see promise.

I grabbed one of the devon note licenses that comes with filling out the macworld survey (if that’s not common knowledge, I forget the link now…I just asume people know about it), so I was wondering what differences devon note will bring to my mac.

What URL is this? I’d love a free DEVONnote license…

See http://www.devon-technologies.com/products/devonthink/comparison.html for a feature comparison with the other DT applications. DN has the same plain and rich text features as the DT applications, good search abilities and AI assistance similar to that of the DT applications.

The text editing functions of DEVONnote, like those of the other DT applications, are simply those of Apple’s Cocoa code in the OS.

So when you create a rich text document in DEVONnote you have the same ruler, styles, alignment, spacing and lists features as those of TextEdit.

A central purpose of the DT applications is the ability to collect and provide access to documents of many file types, and to allow one to search and analyze their information content (especially text and certain metadata).

These DEVONtechnologies applications include contextual recognition features that allow the application to ‘see’ the words in the document being viewed, their frequency, the existence of possible patterns of word occurrence in the document, and comparison of such contextual ‘patterns’ among all of the documents in the database.

The ‘See Also’ button in DN and the DT applications allows one to examine a list of other documents that are contextually similar to the document being viewed.

For example, depending on the content of one’s database, one could be viewing a document about dogs, in which the term “canine” doesn’t appear. Yet the ‘See Also’ operation may see a contextual relationship to other documents in the database that contain the term “canine” and so suggest documents about canines, so that one might see in the list a document about wolves or foxes, in which the term “dog” doesn’t exist.

I find the ‘See Also’ button extremely useful when I’m doing research based on the content of one of my large topical DT Pro databases. Several years ago I wrote an overview-type analysis about potential improvements in the scientific and technical areas to help support better analysis of environmental issues associate with legal and regulatory development – and, conversely, existing legal and regulatory development that cannot be supported by scientific information and are essentially bad law. I received some congratulations about the breadth of my insights. But I cheated a bit, as some of those ‘See Also’ suggestions were the basis of insights I wouldn’t have thought of, myself.

Similarly, the ‘Classify’ button can assist one to organize new content into a database by suggesting relationships to groups that may contain other documents that are contextually similar to the new item.

These artificial intelligence based assistants tend to improve in the usefulness of their suggestions as the size of the database increases. And of course the usefulness of the ‘Classify’ button depends on how well one has started and maintained the similarity of documents ‘filed’ into groups.

I always caution that it remains the responsibility of the user to accept or reject such suggestions. The application doesn’t ‘know’ anything about the user’s area of expertise. The application has no training or knowledge about chemistry, the law, poetry or any other topic in which the user may be interested. Nevertheless, I often find these suggestions very useful to me when I’m looking for new insights about a field in which I do have knowledge and expertise.

Those AI features set DEVONnote apart from other note-taking and ‘snippet’ collection applications. Depending on one’s needs, they may become very useful.

Let’s talk about how the DEVONtechnologies applications recognize and capture the text (information) content of other applications, such as MS Word.

For the most part, DEVONtechnologies uses the ability of Apple’s OS X to read the text content of documents. And the current versions of the DN and DT applications remain compatible with OS X 10.3.9 (which imposes some limitations).

TextEdit can capture the rich text content of MS Word .doc documents (but not, currently, the content of MS Word 2007 documents). But TextEdit cannot capture the text content of files produced b y many common applications, including Pages, KeyNote, Mellel and so on.

Apple’s PDFKit is used to capture the text content (and also render very well) PDF documents, so the DEVONtechnologies applications use PDFKit.

Apple’s WebKit is used to capture the text content (and also generally render very well) HTML and WebArchive documents.

Fortunately, Apple provides tools (including AppleScript and Automator) that allow one to capture any printable document type, e.g. Excel, Word, Mellel, Pages and so on, as a PDF file that contains the text content of the original document and renders it well.

So I can capture the text of any printable document into a DT series database, and make it available for searching and analysis in my database.

Remember, though, that DEVONnote cannot store PDF or image files.

So there’s a Tower of Babel out there, with a great many file types not readable by the DN and DT applications. DEVONtechnologies doesn’t have the resources to develop capture and rendering of all those file types, and in many cases the file types are proprietary and the tools to render them would require re-egineering by DEVONtechnologies. That’s a problem for other developers (and users), as well. Can MS Word read a Pages file?

For the DT series, PDF conversion is currently the most universal approach to bringing into one’s database information contained in otherwise unreadable files.

In the future, DEVONtechnologies will continue its primary focus on enabling searching and analysis of the information content of files in a database. Additional file types will be recognized for capture of information content. Although rendering of some currently ‘unknown’ file types will often be reasonably good, the primary focus will remain on capture of information content. And there will be many other new features and enhancements.

That free copy of DEVONnote is available as a reward for participating in a fairly extensive survey concerning MWSF 2007 at http://www.idelphi.org/.

I don’t think you can get at the free download/license code without taking the survey. :slight_smile:

Thanks, Bill. As far as surveys go, at least this one asked interesting questions.