The Athens service will be withdrawn on 31 July 2008.  Here's what you need to do to ensure that you can access legal databases afer 31 July.

If you're on campus:   You will not need a username and password for Lexis or Westlaw during the next few weeks.   However, the web address for Lexis (and possibly Westlaw) will change. Please follow links from the Law Library's web site or Oxlip rather than your own favourites or Google.

Be sure to cancel your Lexis alerts before 31 July. You will not be able to cancel them after that date but you will keep receiving the e-mails! > more.

Off campus?

Lexis and Westlaw off campus:   You will  need to use the VPN to access Lexis and Westlaw after 31 July.  Please see our VPN instructions for more information.   Alternatively you can use "the Westlaw" password.   A reminder of this has been sent to the Faculty mailling list.   If the VPN doesn't work for you please contact us and we will make alternative arrangements for you.     

HeinOnline, Justis, Social Science Citation Index, Zetoc & CSA off campus:   You  will be able to log in to these databases using your Oxford Single Sign on (OSS) username and password (same as Webmail).     When you link to these databases you will probably be taken straight to a login page asking for your OSS details. If not,  look out for links to "UK Access Federation",  "Shibboleth" or "Academic log in".    Alternatively you can use the VPN instead of using your OSS.   Again if you can't log on to any of thee databases please contact us.

All databases: the URLS of some databases will change over the next few weeks. Please follow links from the Law Library's list of legal databases or Oxlip rather than using bookmarks or Google.

Drizzle project plans a stripped-down MySQL [From Drizzle project plans a stripped-down MySQL]

Here are the instructions on exporting references from EBSCOhost databases, such as Academic Search Premier, into EndNote:

• Perform a seach in Academic Search Premier via EBSCOhost.
• Select the references at the search results page by clicking on "Add to folder" right below each citation.
• After selection, click on "Folder View" on the right column.
• Select all the references that need to be exported into EndNote.
• Click on the icon for Export (the icon with a right arrow)
• "Remove these items from folder after saving" appears. Indicate whether you want to empty the folder of all items after saving by checking or unchecking the box next to it.
• Under " Save citations to a fie formatted for", please click in the radiobox next to " Direct Export to EndNote, ProCite, or Reference Manager". Then click on the Save button.
• Your EndNote program will automatically be launched for you to choose your library.
• Choose the EndNote library by clicking on the library and then on the Open button. Your references will be exported into that library.

All services are expected to be restored by Tuesday 28th July,2008.

Thank you for your patience.

Abstract
Within a short span of fifty years, information technology (IT) has started bringing into being a new technology—the knowledge technology (KT). Experts are forecasting that knowledge controlled and manipulated by computers would be the focal point of power in tomorrow’s world. It looks like, as IT has changed the industrial society into information society, the knowledge technology would change the information society into knowledge society.
Like the IT workers, a highly skilled workforce of knowledge workers would be required to produce knowledge products and manage entire knowledge handling processes.  The knowledge workers should have expertise in: defining knowledge products, identifying knowledge elements, representing them as a knowledge object (software object) and implementing the processes that may be required to manage the knowledge objects in information or knowledge systems. The knowledge product defining ability can be developed among the knowledge workers by creating an environment having high computer literacy rate and well developed information and information technology infrastructure., The knowledge system engineering ability—that involves knowledge element identification, knowledge representation and knowledge element manipulation—can be developed through well focused education systems and well defined training procedures.
To be innovative the knowledge workers would have to continuously update their knowledge and skills. In order to develop these abilities in knowledge workers the teaching and learning processes need to accommodate processes that will enhance the innovative and creative abilities through life long learning. In this paper we attempt to identify the body of knowledge and infrastructure that may be required to educate and train such knowledge workers.

Introduction
Although the term Intelligent Machines for computers was introduced by Alan Turing in late 1950s (Reddy, 1996) but computers still fail to understand and handle unexpected situations. They are weak in reasoning about vague or imprecise situations and they cannot organize their knowledge like we human do.
However, for more than five decades, researchers from the field of AI are trying to build these abilities in them. To achieve this, resources of almost all the fields of knowledge are being applied to capture the concepts that may be required to represent and organize knowledge. Knowledge from disciplines like Psychology, Epistemology, Ethnology, Neurology, Cognitive Psychology, Pedagogy, Computer Science, Mathematics and Statistics has been very effectively applied to explore the underlying facts and deduce from it concepts that may be required to extract, represent and organize knowledge (Desfray, 1994). These efforts have not only moved AI out of its infancy (Grand, 1994) but also have given tools and techniques that are already creating intelligent software products. Consequently we are continuously observing technical and cultural changes.  These changes are creating new form of technology which is being referred to as the Knowledge Technology (KT).

The Knowledge Technology is expected to create knowledge economy in which knowledge would be the basic commodity and knowledge generation, production of knowledge products and their commercialization would create wealth. The knowledge economy would grow with the accumulation of knowledge. Information Systems and Intelligent Systems would systemize and expedite the knowledge creation and accumulation processes. The products of knowledge economy are data, information, information systems, knowledge, meta-knowledge, intelligent systems, and hardware and software tools. Software products would be the most important commodity of knowledge economy.

Innovation would be the key to success in knowledge economy. The reproduction of knowledge products will lead to nowhere. Therefore, societies must invent new knowledge products, if they want to succeed.  In order to attain some degree of success, a knowledge society must have infrastructure like efficient telecommunications systems; high computer literacy rate; well developed information and information technology industry; strong communications and media industry, and focused education and training systems that would prepare a special class of workforce of knowledge workers—a workforce that must be innovative. Therefore, we must focus in all aspects of education and training of knowledge workers in order to develop in them abilities of conceiving, creating and using knowledge products. The education and training requirements of knowledge workers would drastically differ from the workforce of traditional economies including the most recent IT economy.  In this paper we attempt to identify these difference and present structures and contents of such education and training program that may be effective in training the innovative and creative knowledge workers. By structure, we mean the required infrastructure as well as the structure of the curricula, and contents signify the body of knowledge that should prove beneficial in preparing innovative and creative knowledge workers.

In Section 2, we present the evolution of the body of knowledge of computer science. In Section 3, we give characteristics of knowledge technology and formally describe the concepts like data, information, knowledge and wisdom that are essential to understand the nature of knowledge technology. We present the body of knowledge for knowledge technology in Section 4 and in section 5 we give an infrastructure that may support the education and training of knowledge workers. We conclude the paper in Section 6 with a discussion on the impact of knowledge technology and need for educating knowledge workers according to the body of knowledge identified in Section 4.

Computer Science: Body of Knowledge
The work on developing a model computer science curriculum began in early 60's when new departments were being established. The Association for Computing Machinery (ACM) published first Curriculum '68. Within a decade, rapid changes in computer science forced to design Curriculum '78 in which the core knowledge of computer science as a discipline was defined from the following nine areas:

• Theoretical Computer Science
• Algorithms
• Architecture
• Databases
• Systems
• Programming Languages
• Human Computer Interface
• Artificial Intelligence
• Societal Aspects of Computing

The fast changes in computer hardware and software technologies forced to update and revise the curricula throughout 80's and it resulted in Curriculum '91. In where, based on the technological advancement the body of knowledge associated with computer science was identified as:

• The World Wide Web and its applications
• Networking technologies, particularly those based on TCP/IP
• Graphics and multimedia
• Embedded systems
• Relational databases
• Interoperability
• Object-oriented programming
• The use of sophisticated application programmer interfaces (APIs)
• Human-computer interaction
• Software safety
• Security and cryptography
• Application domains

The technological and sociological changes continued and their influence resulted in Curricula 2001 (Computing Curricula Report, 2001). In Curricula 2001 the body of knowledge was developed for fourteen knowledge focus groups and six pedagogy focus groups shown in Table 1 below (IEEE Computer, 2001).
Along with the curriculum design, efforts to define the computer science as a discipline continued. In (Denning, 2001a) Peter J. Denning describes: "computer science as a discipline that studies the phenomena surrounding computers." By phenomena he means: "design of computers and computational processes, representations of information objects and their transformations, hardware, software, efficiency, and machine intelligence." According to him the computer science discipline (or computing) is called "informatics" in Europe.

He grouped the computing discipline into IT-specific disciplines, IT-Intensive disciplines and IT-supportive occupations groups. He considers these groups constitute the emerging Profession of Information Technology and gives the detailed description of each element (Denning, 2001b).

Advances in technology as well as cultural and sociological changes are influencing the computer science education.  As a result computer science body of knowledge is continuously expanding in disparate areas. To impart the knowledge of a particular area several education programs are being offered under the name of Computer Science, Computer Applications, Information Systems, Information Technology and the like.
At present, we are witnessing exponential increases in computing power, rapid growth of networking, multimedia and computer gaming, and evolutionary computing that includes knowledge discovery and data mining. The technological changes induced sociological changes. The together are forcing continuous revision of computing or IT related curriculum and design of education program to meet the ever changing manpower requirements. One of the areas that is emerging very fast and influencing societal aspects is Knowledge Technology. The Knowledge Technology   has always been one of the components of computer education. It was identified as Artificial Intelligence in the very first computing curriculum, and now it has expanded into a long list of subfields. Table 3 shows the list of some important subfields of Knowledge Technology.

Knowledge Technology
It is hard to define knowledge but we can say knowledge is awareness about useful or harmful information gained through experience or learning. The experience or learning gives knowledge about the underlying object or phenomenon and tools that may be used to handle the underlying object or phenomenon. In this context we can say that the knowledge technology is the technology that gives the learning ability to a device (or intelligent systems in general) and creates tools and techniques for transforming information into knowledge and knowledge into wisdom.  Wisdom is awareness of the useful knowledge.  Fig. 1 shows the structure of the knowledge systems which depicts the relationships between information technology and knowledge technology.

The information technology facilitates the knowledge creation process. It provides effective and flexible processes for data management and information extraction.  These two processes collectively constitute the Information System that essentially transforms the observed data into information.  The intelligent system transforms information into knowledge and wisdom. These systems discover knowledge from information, deduce wisdom rules from knowledge, and use these entities to their advantage.

The thinking ability of the intelligent systems gives them power to apply existing knowledge, generate new knowledge, transmit knowledge and work with knowledge effectively.  Such systems help in knowledge accumulation and creation and maintenance of intellectual assets like digital book libraries, computer software libraries, digital (still/video) image databases, databases of useful observations, and so on. Usage of intelligent systems strengthens the knowledge economy because they themselves are the items in the inventory of the knowledge products.

As mentioned before, the data management process involves capturing, gathering, organizing, storing and retrieval of data elements. In this section we define the meaning of information in the context of information processing. In this context an information extraction process associates known concepts that are embedded in transformation rules with the data elements.  Using the extracted information from the data, the knowledge discovery process discovers knowledge and deduces rules of wisdom.

Observations yield data or facts. We use symbols to represent data. The sequence 08 09 07 08 00 20 05 13 16 05 18 01 16 20 21 18 05 of digits (symbols) 0 to 9 is an example of data.  A transformation when applied on a data set yields information.  Suppose in the above sequence every pair of symbols represents a letter.  For example the pair (01) represents letter 'A', (02) represents letter 'B', …, (26 ) represents  'Z' and (00) represents a blank.  By applying the transformation (given below) on the sequence, we obtain the text string 'HIGH TEMPERATURE'. The string conveys information about the measure of the temperature of some entity.

Consider a temperature measuring device has been installed in a hospital to monitor the temperature of patients. The device has observed this data sequence.  If the device has the ability of transforming the data into information, it may transform the recorded data into information 'HIGH TEMPARATURE'. We can make this device intelligent if we make it learn the concepts like 'high temperature increases the chance of death' and 'call a physician when there is an increased chance of death.' These concepts are knowledge. They are gained from experience. We can make the device to acquire this experience over a period of time or learn them from a teacher.

Knowledge Technology: Body of Knowledge
The knowledge technology is the technology for discovering and managing knowledge. The automated knowledge discovery process involves information system as the front-end processor that extracts information from the data. The body of knowledge required to create the front-end processor is the body of knowledge that has been developed for traditional computing or informatics.

The back-end processor deduces knowledge from information and learns laws of wisdom from the extracted knowledge. The knowledge management is the process of making the best use of knowledge, organize it and create new knowledge.

In addition to the above mentioned body of knowledge, knowledge from the disciplines like Psychology, Epistemology, Ethnology, Neurology, Cognitive Psychology and Pedagogy also need to be included in the knowledge technology curriculum.

Knowledge Technology Learning Environment
Educating knowledge workers is a very challenging task as they are expected to update their knowledge continuously. This continuous or lifelong learning is a new dimension that information technology and knowledge technology are adding to the education. In this system teachers locate the knowledge source and guide the learners to the right knowledge source.  They prepare personalized learning plans. Teachers are themselves lifelong learners. On the other hand learners learn by doing and by interacting with each other. The performance evaluation guides learners towards improvement in future.  The learning opportunities are open to learners over the lifetime.

To attain this objective we need well structured and integrated environment, as shown in Fig. 2 below, for efficient teaching and learning of the knowledge workers. The environment integrates text, pictures, video, and audio components of learning material, as well as simulation facilities capable of depicting concepts through animation. Of course, all these elements should be interconnected through an efficient communication network control and manage by computers.

The efficient use of computers is strengthening the information societies day by day. These societies are continuously gaining expertise in information and knowledge processing. This process is gradually placing them in dominating positions in the arena of world power, hence continuously widening the digital divide gap.  Now, knowledge-divide, induced by the knowledge technology, is further strengthening them because they can create and apply knowledge effectively. This trend poses new challenges to the thinkers, educators and administrators of all the societies to formulate effective policies and discover processes to prepare their societies that can meet the challenges.

The challenges are due to the unique nature of knowledge economy because it progresses with the new technologies and it allows sharing information and knowledge at the speed of light.  These challenges can only be met with the efficient force of knowledge workers. Here efficient means: the knowledge workers must be creative.  This force can be prepared through investment on education and on creation of life-long learning and research and development environment.

In knowledge economy there is no limit to the area of activity. Workers from every walk of life can be trained as knowledge workers, but they must have enhanced creative ability that can be attained by focusing on basic education with emphasis on information and communications technology, lifelong learning and creation of environment where technology is easily available and used.

In order to compete in the knowledge society we need strong institutions with high quality human skills and infrastructures.   The body of knowledge presented in this paper can be used as a guide to define the curriculum that may be designed to impart proper knowledge. To integrate the varied knowledge resources we must have a flexible yet fast communication network, as suggested in this paper, in which knowledge can be propagated and accessed timely.

No?

How can you reach here if you want to? forget about the other keywords that might bring you to this place

Any idea why?

Spelling mistakes!!

This is the major reason why we and the examiners miss out lots of relevant prior art.

While choosing the name of the blog I mistyped as I was in a hurry and even after wordpress confirming the name from me 3 times I missed it (happens). Similarly, there are various such patents that include such words that get missed out even after multiple quality checks.

Therefore, now next time when you search keep spelling variations in mind and include all the possible word variations in your (keystrings or keystrngs or keystings or kystrings).

Some of the changes in the new version include:

• references can be more easily catagorized into groups - easier to organize your references in a single library rather than using different libraries for different topics
  

• The reference preview now displays active URLs for quick access.

• Updated documentation, Output Styles, Connections and Import filters.

So, when I suggested we search advertising trade publications in LexisNexis Academic, Alex balked. He understood "in the library" to mean publications physically housed in the library's collection. He envisioned flipping through print issues of whatever magazines I would suggest.

I'm a professional librarian, an expert on online research strategies and resources, an adjunct instructor of database and Web search skills at a major university. I've lectured and published extensively on research issues. Yet I've failed to convey what a library is to my son. Shame on me.

What his instructor meant was, use established industry-recognized sources. The reason he wrote "in the library" is because this is where students may reliably find such sources. In today's world, however, students may benefit from the library's guidance without ever leaving their dorm. They may access thousands of databases by logging in to their school's library Web site.

If you aren't a student, a relatively new sister product to LexisNexis Academic, called LexisNexis Library Express, as well as other reputable databases, may be available to you through your local public library. Check out the library's Web page.

Identifying useful databases and constructing productive queries is a lot more work than searching Google. The reward is the quality of the information you find. This isn't to say you can't find information of quality through Google. But databases selected by your library - whether a school, public or corporate library - will consistently provide the kind of information you can rely on.

This was the teacher's point. He wasn't being old-fashioned or a stick-in-the-mud. He was trying to lead students to the resources they will have to use as young professionals.

What does this have to do with historical fiction? It has so much to do with it, I can't discuss it all in one posting. For now, suffice it to say that the quality of a historical novel depends in large part on the quality of the research into the historical place, event or person. If the author doesn't have an accurate understanding of the history, this fact will turn up in one form or another in the story (e.g., the many anachronisms in Pillars of the Earth).

However, until the faulty hardware is replaced, all Digimap Collections will remain unstable and may become unavailable at any time. Engineers are monitoring the service closely, and further information will be posted when available.

Lecture Notes in Computer Science (LNCS) has recently published its 5000th volume!

Since it was first established in 1973, LNCS has provided the computer science community with a continuous channel for cutting-edge developments in the field. Initially launched as a series focusing on theoretical computer science and research advances in Europe, LNCS has evolved into one of the world's most authoritative computer science research forums, covering the latest results from all areas of computer science and information technology research, development, and education.

LNCS 5000 features an exciting theme authored by distinguished researchers.
Edmund M. Clarke, E. Allen Emerson, and Joseph Sifakis are recipients of the ACM Turing Award 2007 for original and continuing research in a software/hardware quality assurance process known as "Model Checking." We are pleased to publish their contributions in "25 years of Model Checking", the anniversary volume.

LNCS is one of the leading resources in IT for conference proceedings & books so worth having a look around it: http://www.library.qut.edu.au/find/databases/fullrecord.jsp?id=4993

But upon clicking a trusty Ebsco database, what shall appear? A new look, an unfamiliar database. In these few moments of blinding terror my fears began to materialize...would I stagger through this session leaving the patron unsatisfied with her database introduction and I scrambling for cover?

Egads, I thought aloud, while inwardly struggling to get a grip on what professionalism was left of the situation. Must be Ebsco's switch to its new interface, I stammered. Strange that it had to happen at the very moment I was demonstrating the basics of simple searching.

Steeling my resolve I proceeded to instructually technologize until sufficiently confident the patron was prepared. Afterwards I made a more thorough investigation of the new look, and so I have found:

• simplified interface, though seeming stretched. At the very top of the screen one will find the options for publication, cited references and subject terms searches. Don't know why it was placed at the top...maybe they could have been placed strategically under the main search box next to the advanced, visual and search alert options.
• more intriguingly, the addition of the "visual search" is a nice touch. After initial confusion of wanting to search within the visual area, the user is able to build upon their search simply by scrolling with the mouse to find subjects and articles in a hierarchical manner with a minimum of clicks.
• more thumbnails and image options highlighted. Kinda resembles a Yahoo! or Google News search retrieval.
• the options for opening full-text in pdf or html, as well as the options for saving, exporting, citing in various formats and adding to a folder are definitely more predominantly placed, both at the top and bottom of the citation records.

Overall, not a whole has changed with the functionality, but in an effort to make researchers less intimidated, Ebsco has certainly emphasized the older features in a shinier display...bolder and more interactive scrolling.

Definitely worth looking at before those instructional sessions start.

The next time you access ISI Web of Knowledge, you'll find enhancements that provide you with totally new options for research:

Citation Mapping • Be the first to see the beta version of this powerful new Web of Science® visualization tool. Visualize citation relationships and understand the meaning of a cited reference search. Map citations by author, institution, country, subject, and more!

Additional All-Database search options • Now you can sort by Times Cited* and search for specific addresses within an All-Database search, making this powerful feature even more flexible and convenient.

New 2007 Data for Journal Citation Reports^®** • The new 2007 data provides the most current information available to determine a publication's impact and influence in the global research community.

More patent coverage • Derwent Innovation Index** now provides more extensive coverage of Canadian patents.

Collaborate and share material easier with EndNote^®Web • Designate read/write access for shared EndNote Web folders. Link to the full text of articles directly from EndNote Web records.

Unique DOI number • View the DOI number in the full record and after export to bibliographic management tools.

Shibboleth support • ISI Web of Knowledge and EndNote Web are now compliant with all Shibboleth regulations.

I recently shared the with my department about the TexShare databases that are available for free searching through local public libraries or online from anywhere using a user name and password obtained from local public libraries. The above video posted on YouTube is a good introductory marketing tool for the service. Periodic unsolicited information sent to patrons from library resources highlights and reinforces the value of library and/or information services.

Index
Je kunt  op verschillende manieren proberen een auteur te zoeken:

1. Search fields
2. Advanced search Author search
3. Basic search

Via de 'Search fields' kun je een achternaam intikken, veld AU aanvinken en dan op 'Search' klikken, maar dan gebeurt er niets: je blijft het veldoverzicht te zien krijgen. Het enige wat helpt is op de 'Display indexes' te klikken en dan krijg je alle auteurs vanaf voorletter A: dan mag je aanklikken welke je wilt. Dat is nog wel te doen als je een weinig voorkomende naam hebt, en/of de voornaam weet. Maar dan nog: Davis, M. levert bijvoorbeeld drie pagina's vol namen (in Psycinfo 1806-2008 ) op die je alle 180 stuk voor stuk mag gaan aanklikken  :-( . Er is geen optie: klik alle auteurs op deze pagina aan.

Je kunt bij 'Advanced search' klikken op de auteursindex en dan de gegevens invoeren.  Bij de instructie staat dit:

Enter the Author's last name, a space, and first initial if known:

Als je op 'Search' klikt krijg je ook hier de hele index te zien, en daar moet je vervolgens alle voorletters aanvinken waarvan je denkt dat ze erbij horen ...
Maar ga er maar aanstaan als je geen initialen weet, of een veel voorkomende naam hebt.

Dan komt de behoefte aan een truncatie in beeld, maar hoe?

Truncatie
Het truncatie teken was voorheen alleen een $. Op zich al onhandig, want veel systemen gebruiken daar een * of een ? voor.  Dus bij het lanceren van het nieuwe systeem was ik dan ook blij dat nu de * 'ook' mocht.
Bij de Keyword zoekactie staat:

Enter Keyword or phrase (use "*" or "$" for truncation):

De slimmerik die denkt dat dat ook voor auteur zoeken opgaat heeft maar deels gelijk, want als je denkt dat je Author aan kunt klikken en dan Davis* in mag tikken krijgt als resultaat 0 hits met de mededeling:

"root davis*".m_auts.

en als je Davis$ intikt krijg je weer de index :-( .

De Truuk
Er is natuurlijk wel een truuk voor, en dat is deze: de achternaam, een spatie om aan te geven dat er geen letters meer achter komen, een $, een punt, AU als veldcode en weer een punt. En omdat je de veldcode erbij zet, mag je dat zowel bij Keyword invoeren, als bij Author. De subset Author aanklikken heeft hier dus geen voordeel.
Dit zijn dus de resp. mogelijkheden voor Davis-zonder-initialen en A. Davis met-misschien-meer-dan-een-enkele-A-als-voorletter:

davis $.au.

davis a$.au.

Maar wie verzint dat nou uit zichzelf? Ik krijg min of meer wanhopige kreten van onderzoekers dat men geen auteurs kan vinden, en het aanklikken van iedereen ondoenlijk vindt.

.. en zo komen je gebruikers er dan toch toe om maar de basic search te gebruiken, wat je ze aanvankelijk had afgeraden ...

Er is wel wat veranderd
Voorheen was het zo dat zoeken op Davis.au.  alleen  "misbaksels" opleverde, namelijk referenties waarin de auteur géén initialen heeft, maar die kom ik nu, in PsycInfo althans, niet meer tegen.
Als je ze in de Medline of een andere database nog ziet, geef me dan een seintje.

Academic Search Premier
Avery Index to Architectural Periodicals
Biological Abstracts
Business Source Premier
Communication & Mass Media Complete
EBSCO Animals
EconLit
ERIC
Food Sceince and Technology Abstracts (FSTA)
Funk & Wagnalls New World Encyclopedia
GreenFILE
Health and Psychosocial Instruments (HAPI)
Health Source – Consumer Edition
Health Source – Nursing/Academic Edition
Inspec
Library, Information Science & Technology Abstracts
MAS Ultra
Mental Measurements Yearbook
Military & Government Collection
Newspaper Source
Philosopher’s Index
Primary Search
Professional Development Collection
PsycARTICLES
PsycEXTRA
PsycINFO
Regional Business News
Teacher Reference Service

Have questions on new features or searching any of these databases?   Librarians are available to assist you.  Stop by the reference desk on the upper level of Galvin to get personalized research help.  If you can’t make it in, you may phone, IM or email librarians from the convenience of your home or office.  See the Ask a Librarian page for contact information.

Direct link to the video only: https://webmeeting.nih.gov/p91519064/

A good coverage is given by Michelle Kraft (Krafty Librarian) at her site (click here).

The clinic, presented by Katherine Majewski, updated recent changes to PubMed, earlier described at the NLM information bulletins on the new ATM and the Beta Advanced Search page.
Recent changes have also been amply described (and discussed) at several of my previous posts, most notably this one.

Here is an overview, with emphasis on new aspects (at least to me).

Citation Sensor:

In the clinic the citation sensor was defined as: "a new feature designed for users seeking specific citations". However it is not a separate search box. The citation sensor works automatically when you type words into the general search bar. If combination of words are recognized as representing citations (e.g. volume numbers, author names, journal titles) the matches are displayed in a yellow box above the retrieval.

In my previous post I already discussed that the sensor doesn't always work perfectly and like Krafty, I think that the Single Citation Matcher (in the blue side bar) performs better. It suggests author and journal titles as you write them. Furthermore, you can just fill in the specific information you know in specific fields, i.e. if the author name is misspelled/wrong, it often suffices to fill in year, page number and title word(s), to name just one possible combination. In response to a question, Majewski said the sensor is not an advantage per se as opposed to the Single Citation Matcher. Probably it is just handy for people used to a Google-like way of searching.

One thing new to me was that there are two "Details" when performing a search.

When you type: choi blood 2008, the citation sensor finds 6 hits, 3 of them shown in the yellow box.
The Details button shows: choi[All Fields] AND ("blood"[Subheading] OR "blood"[All Fields] OR "blood"[MeSH Terms]) AND 2008[All Fields].

However when you click 6 articles to see them all, the Details button shows how the citation sensor has translated the search in: choi[Author] AND (blood[Author] OR "Blood"[Journal]) AND 2008[Publication Date]

Thus in fact the search is translated twice (although the citation sensor-results are always a subset of the full results). If you click on 6 articles, the 2nd translation appears as a 2nd search in the Search History.

ATM - Automatic Term Mapping.

ATM has been changed in conjunction with the citation sensor in order to identify queries that contain citation-type information. The old ATM mapped search terms to subject, journal, and author tables in that order. If a MeSH-match was found, PubMed would search for that MeSH as well the user-input as a textword (title, abstract). Automatic term mapping would then stop because it found a match with MeSH. Thus terms that are not only in the MeSH but also in the author or journal table would have been missed, such as in Burns Laryngoscope 2005. The old ATM would map Burns and Laryngoscope as MeSH (subject-search), but the new ATM also searches these terms in 'all fields', thus enabling the retrieval of the paper of Burns in Laryngoscope.
In the Q & A part of the session Majewski advised to use qualifiers as MeSH when Burns is searched just as a topic. I only wonder if/how most of the untrained people would find this out.

Another consequence, not really addressed here, is that multi-term words are split and searched individually. With the new ATM, gene therapy is not only searched as the phrase gene therapy (as MeSH-term and textword) but also as ”gene”[All Fields] AND “therapy”[All Fields], which leads to a far greater retrieval (almost 250%). Few of these extra hits are relevant. (see previous post)

Statistics, however, show that the thousands ('real') queries performed returned only 10% extra hits on average (see ATM-FAQ for more information). According to NLM, the enhanced ATM and citation sensor have considerably improved searching PubMed. Probably because most people just come to PubMed to search a specific paper or subject (running one or two search commands). The new features enhance citation searches, while subject searches do not suffer too much as long as multiple terms (concepts) are used, as this will filter much of the noise seen with one term (because the term is searched within the context of the other word).

My remark that most of my patrons do do subject searches was interpreted as "do do broad searches". Which in effect they do (i.e. searches for systematic reviews), but I do not think the suggested NCBI books might be very helpful to them, although it might indeed serve those people (patients?) that want information about broad subjects like "burns". Perhaps PubMed/NCBI can offer subject searchers other tools as well.

Notably, based on user input there are now (as of July 2nd) some exceptions to the new ATM-rule:
Substance names (such as ferrous glucanate) and MeSH with stand alone letters or numbers (like complement factor B) will not be broken apart, but searched as a phrase.

Advanced Search (Beta-version)
Advanced Search is amply discussed in a previous post. However, I didn't mention that the page consists of 4 collapsible boxes beneath the Search Bar (I missed this: you have to click a small minus sign at the upper left of each box in order to collapse.) In essence you can search by many fields, the default fields displayed being Author, Journal, and Publication Date (box2) and all fields (box 4). There is an index for each selected field available (little buttons right of the search boxes). I see no other difference between box 2 and 4 than the defaulted field and the fact that you can only make multiple choices from the index in box 4. Answering a question in the audience Majewski said they might consider allowing multiple choices in box 2 as well.
Box 3 shows limit-options, much the same as the Limit-tab in the usual frontpage, except that you can unlock your limits to future searches using the lock icon (by defaulted limits are carried to future searches).

Thus again this new 'enhancement' mainly facilitates citation searches, not subject searches. Clinical Queries are absent and it is for instance not possible to look up any MeSH other than by index, and even this often goes wrong with multi-word terms. The question why MeSH-trees were unavailable in the beta-version remained unanswered at the clinic.
It was a relief though to hear that there were no intentions to replace the normal PubMed frontpage by this advanced search page in due course.

Katherine Majewski ended the clinic by saying that answers to the questions posed during the clinic would be shown at this NLM-page later. She also encouraged to give positive and negative feecback by writing to the NLM customer service and to be as specific as possible if your search was negatively affected by the recent PubMed changes.

-------------------------------

De video van de PubMed Search Clinic, die ik in een eerder bericht aankondigde is nu te zien op: http://www.nlm.nih.gov/bsd/disted/clinics/pmupdate08.html.

Directe link naar de video: klik hier

Michelle Kraft (Krafty Librarian) heeft de clinic al goed op haar blog samengevat.

De webpresentatie, gegeven door Katherine Majewski, behandelde de recente PubMed-veranderingen, zoals aangekondigd in de NLM informatiebulletins (gewijzigde ATM-mapping resp. Beta Advanced Search)
Eerder heb ik deze veranderingen ook al uitgebreid beschreven en becommentarieerd. (zie bijv. hier).

Hier een samenvatting, met nadruk op nieuwe aspecten

Citation Sensor:

In de webpresentatie werd de "citation sensor" omschreven als: "a new feature designed for users seeking specific citations". Het is echter geen aparte zoekoptie. De citation sensor doet zijn werk automatisch als je woorden in de algemene zoekbalk typt. De als citaties herkende hits worden apart op een gele achtergrond getoond.

Eerder heb ik al opgemerkt dat de sensor niet altijd goed werkt en evenals Krafty denk ik dat de Single Citation Matcher (in the blauwe balk) veel beter werkt. Deze geeft nl. woordsuggesties terwijl je typt en je kunt elke mogelijke informatie specifiek invullen. Weet je een auteur niet dan kun je vaak volstaan met jaar, paginanummer en titelwoorden, om maar één combinatie te noemen. Volgens Majewski is de sensor ook niet perse beter. Waarschijnlijk is het vooral handig voor mensen die gewend zijn aan een Google-zoekwijze en die verder weinig weten van PubMed. Zelf zou ik toch wel graag willen dat je de citation sensor naar believen aan of uit kon zetten.

Ik zag nu pas voor het eerst dat je 2 "Details" hebt, als de citatie-sensor iets mapt.

Typ je: choi blood 2008, dan vindt de sensor 6 hits en toont er 3.
Onder Details is te zien dat Pubmed de search vertaald als: choi[All Fields] AND ("blood"[Subheading] OR "blood"[All Fields] OR "blood"[MeSH Terms]) AND 2008[All Fields].

Als je op 6 articles klikt om ze allemaal te zien, staat onder Details hoe de citatie-sensor de search vertaald heeft: choi[Author] AND (blood[Author] OR "Blood"[Journal]) AND 2008[Publication Date]

Dus, er zijn eigenlijk 2 'vertaalslagen' Als je op 6 articles klikt dan verschijnt de 2e mapping als een zoekset in the zoekgeschiedenis.

ATM - Automatic Term Mapping.

ATM is evenals de citatie-sensor ontwikkeld aangepast om zoekacties gericht op het vinden van artikelen te vergemakkelijken. De oude ATM stopte met het zoeken van termen in de MeSH-, auteurs- en tijdschriftenlijst als een passende MeSH was gevonden. Tevens werd het ingetypte woord als tekstwoord gezocht. Met als gevolg dat termen die zowel in de MeSH- als in de auteurs- of tijdschriftenlijst voorkwamen nooit anders dan als MeSH (en tekstwoord) werden gezocht. Met Burns Laryngoscope 2005 zou dus nooit het artikel van Burns in Laryngoscope zijn gevonden. Met de nieuwe ATM lukt dat wel.
Majewski adviseerde om veldenaanduidingen (qualifiers). zoals MeSH te gebruikenals je op een onder onderwerp zoals 'Burns' wilt zoeken. Dan vraag je je wel af in hoeverre de gemiddelde Pubmed -gebruiker dit weet.

Tijdens de sessie werd niet echt aangekaart dat termen die uit meerdere woorden bestaan worden opgesplitst en in alle velden worden gezocht. Eerder heb ik al laten zien dat bij de nieuwe ATM 2,5 x meer hits oplevert met een term als gen therapie en dat de meeste van deze hits weinig relevant zijn.

Volgens de NLM statistieken leiden echte zoekacties gemiddels slechts to 10% extra hits (zie ATM-FAQ voor meer info) en zijn zoekacties door de vernieuwingen aanzienlijk verbeterd . Waarschijnlijk omdat de meeste mensen alleen maar snel even iets opzoeken (1-2 zoekopdrachten) en vooral geinteresseerd zijn in specifieke artikelen. Wat dat levert het intypen van wat termen in de zoekbalk nu eerder wat op, en zolang je veel termen met elkaar combineert heb ik ook niet veel last van veel ruis bij het zoeken op onderwerp. Maar ik ben zeker niet overtuigd dat dit het zoeken op onderwerp verbetert.

Mijn opmerking dat mijn klanten vooral op onderwerp zoeken werd opgevat als dat ze vooral breed zoeken. Nu is dat wel zo, maar ik denk niet dat zij veel aan suggesties hebben als NCBI-books. Dit lijkt me wel geschikt voor mensen die zich globaal willen inlezen in een onderwerp als brandwonden (burns), patienten bijvoorbeeld. Misschien heeft PubMed/NCBI wel nog andere tools voor uitputtende searches in het verschiet....

Op basis van gebruikersfeedback zijn er vanaf 2 Juli wel enkele uitzonderingen op de nieuwe ATM-regel, t.w.:
Substance names (zoals ferrous glucanate) en MeSH with losstaande letters en cijfers worden niet langer opgesplitst, maar als phrase gezocht.

Advanced Search (Beta-versie)
Advanced Search heb ik ook eerder uitgebreid besproken (zie hier). Wat ik nu pas bemerk, is dat de velden onder de zoekregel in-en uitklapbaar zijn. Er is een miniscuul min tekentje helemaal linksboven elk veld, waar je op moet klikken om het veld te verkleinen.

De essentie van advanced search is dat je veel verschillende velden kunt doorzoeken, maar dat de standaard velden weer citatie-gericht zijn, dus: Author, Journal, and Publication Date (veld 2) en All Fields (veld 4). Je kunt termen voor elk gekozen veld opzoeken in een index (klein knopje rechts). Ik zie eigenlijk geen verschil tussen veld 2 en 4, behalve dan het standaard veld en het feit dat je in het 4e veld verschillende termen tegelijk kunt aanklikken. Mogelijk komt deze optie ook voor veld 2.
In veld 3 kun je limieten aanklikken, eigenlijk erg vergelijkbaar met de Limit-Tab op de PubMed openingspagina. Wel prettig dat je een limiet desgewenst alleen gedurende één zoekactie kunt toepassen (default: blijft alle zoekacties aanstaan).

Dus ook advanced search beta is vooral ten dienste van degene die bepaalde artikelen zoekt. Je kunt bijvoorbeeld alleen maar de MeSH in de index opzoeken en er zijn geen Clinical Queries. De vraag waarom De MeSH-hierarchie niet geraagdpleegd kon worden vanuit bleef onbeantwoord.
Het was wel een pak van mijn hart, dat het volgens Majewski niet de bedoeling was dat de Advanced Search de normale openingspagina op termijn zou vervangen.

Katherine Majewski beeindigde de sessie met de mededeling dat antwoorden op gestelde vragen later op deze pagina zou verschijnen.

Ze verzocht iedereen ook hun eventuele problemen met de veranderingen zo specifiek mogelijk aan de help desk door te geven.

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