Show HN: A new take on academic search
scholr.ly
scholr.ly
I tried some queries and the results were awful.
query: author:"george church" ... I see only one publication, titled "registered trademark of AAAS. Synthetic Gene Networks That Count" which must be wrong.
query: author:"george whitesides" ... again only one publication ("New Editorial Board Chair"), and a coauthor named "Dropspots Microdevice" http://scholr.ly/person/6263228/dropspots-microdevice
Naturally, his affiliation is listed as "for Lab on a Chip".
query: "Rapid casting of patterned vascular networks for perfusable engineered three-dimensional tissues" (the title of a recent paper) returned a few publication results, none of which were the publication in question. It was in Nature Materials, so it's not exactly obscure.
query: doi:10.1038/nmat3357 ... no results found. Hmm.
Well, I don't know how to use this site. Here's what I really want:
* I want a public domain, reusable index of all papers everywhere. I want bibtex, xml, json, and all the other terrible formats for keeping track of those papers.
* I want working Zotero translators that can properly extract metadata from all science publishing sites. And I just want this data instead of having to fish it out of a search engine.
* I want to be told where I can find pdf files hosted on sites, so that I don't have to send emails begging for copies. Google Scholar does this pretty well.
* Actual data about which papers cite what, instead of trusting the "cited by" links/results in Google Scholar. Also, a "this paper cites..." feature so that I don't have to bother digging out the doi numbers from the bibliography myself.
* Supplementary documents are evil, but they exist and they should be immediately available next to or with any paper.
Edit:
* An index of which libraries at which universities are subscribed to which publishers. If anyone wants to contribute to this information, please go to your library's ezproxy service (ezproxy.lib.whoever.edu:2048/menu or sometimes on a different subdomain) and copy/paste to kanzure@gmail.com for aggregation. This is useful for understanding which universities are likely to have access to which papers. Each service listed also has either partial/incomplete subscription and very rarely full subscription, but getting a list of the exact access rights is even harder to squirrel out. Tracking down access to papers is a pain in the butt. ILL is silly and costs way too much ($0.30/query say whaaat).
* I also want an academic aggregator that has the balls to go after OCLC, WorldCat, etc. I wish Bill Gates would just buy the entire scientific publishing industry, but alas! I should emphasize this OCLC alternative would be open-access. Mendeley doesn't count, I can't even get their data out.
I'm definitely neglecting some other major issues..
* each paper page has PDF links and BibTeX
* we extract citation data from PDFs so you can browse the citation graph immediately. We're working on stats right now, but everything we extract is publicly inspectable.
* we're all about open access- in fact, we are only open access, and will do our best to contribute back to bettering academic communication.
* trust me, we have the balls. Still working on the rest.
> we extract citation data from PDFs so you can browse the
> citation graph immediately
Can you just.. give us the citation data instead? How is this better than ISI and other vendors? Edit: removed some other comments. That's my most important question.I really like what Mendeley has done so far. I've chatted a bit with them about integrating with their API, ourselves- it's a rich data source, and I think we could do some great things.
> freely available api for your service, which exposes PDF links
I configured an API like this just the other day (zotero's translation-server). I wanted an IRC bot to fetch pdfs. I call him paperbot. The big problem was figuring out how to extract the right links and metadata from each publisher. But the server seems to work.Re: funny authors- these things happen when you use extracted metadata. I've been fairly successful internally cleaning it up, and will apply those techniques further to the production data soon.
This site is very heavy. Literature reviews are a process of finding the tens of papers you need out of thousands of candidates, and this site gives ten results per slow-loading page. The results take up a lot of screen real estate, and are not optimized for scanning. Whitespace usage seems to be intended as something to make the site look pretty and modern without any particular functional value.
The right column is annoying. The "Authors" heading is way to the right, making it hard to figure out what it's supposed to be. And all enties in the search I did seemed to be labelled "related publications", so it's not immediately clear why it would be headed "Authors". The author pages are pretty slight when you get to them and, again, are not well-optimized for quick visual extraction of information.
The paper page is terrible. Even on my 1920x1200 screen, a long paper name takes up over half the page height. Useful targets (like obtaining PDFs and bib info) are small and hard to find relative to the giant, useless title. And why on earth would one need to click on a "see more" in order to see the full list of citations? When you do click through, the sliding transition holds no value and the list is filled with duplicates (e.g., http://scholr.ly/paper/2887595/enhancing-search-performance-...).
Google Scholar, despite the fact the you can't easily surf citations in both directions, is very useful for hoovering up a large number of papers so their relevance can be assessed. This site is not, and doesn't seem to provide any particular new value in paper discovery. If there's something else going on here, it isn't immediately obvious.
The academic search space has a lot of opportunity for improvement, but for me the interface of this site just adds friction to an already painful process.
Looking for relevant papers involves sifting through a LOT of chaff. For search results, I tend to want focused density in my results, and I want to do as little work as possible to get it.
* Scannable
* Enough context to establish possible relevance
* An easy way to obtain the fulltext of the paper and a .bib entry
As far as scannability... * I'd rather scroll than click.
* I'd rather not scroll than scroll.
The more info I can easily read on each screen, the better, and I want action links with the search result itself. Clicks that go to other pages or sites require leaving a trail of tabs open in the browser to avoid losing the search context. So don't assume that if someone clicks on a link that they want it to open in the same window. I want to whip through all the garbage as fast as possible, and every click and animated expanding box makes that harder.Part of the issue is that search results are only a small part of the paper-finding process, and the poor quality of most results (as well as text buried in PDFs) means that a lot of additional steps are required to assess relevance. I've tried Zotero but don't like being trapped inside it, so have developed my own workflow for capturing and assessing papers:
First, every paper I download gets a unique identifier that is easy to recreate from the paper's metadata, so I can figure out what it is just from a printed hardcopy. The code is similar to the one that Google Scholar used to generate, slightly extended to improve uniqueness. It's not perfect, but I think I've had only three collisions during the time I've been using it.
Second, the paper is saved as CODENAME.pdf in a papers directory, and possibly symlinked to a project directory. I've got a greasemonkey script to automatically route appropriate sites through my university's ezproxy, but the slight differences between IEEE, ACM, and Springer are constantly annoying.
Third, a BiBTeX entry (with the code as the identifier) is appended to a master .bib file. Google Scholar's BibTeX entries are often incomplete, so getting them from the publisher's site is much preferable. Bad entries still creep in, and have to be cleaned up later if it ends up being used as a reference.
Fourth, an entry for the paper is created in an appropriate .org file, keyed with the code. Notes will later be transcribed, and keywords appended.
That's the trawling process. Later, I'll go back and actually sort through all the papers pulled in, to determine whether or not they're really relevant, or might be relevant to another project. This process can either be using a PDF reader (which is painful) or using a large pile of actual hardcopy printouts (which is painful). On Linux, I've yet to find a good way to annotate PDFs, so hardcopy is actually the most useful. As each paper is assessed, I use different colored highlighters to mark the most relevant bits, particularly references that I want to chase (which, for example, get marked with red highlighter). A quick assessment of the value of the paper is scrawled across the front page, along with its code. If it's determined to be irrelevant, a paper can be discarded at any point in the process.
Highlighted references are chased during another trawl. Each reference has to be entered by hand into Google Scholar, since it doesn't let you surf the reference chain directly. (MSR's fancy bits are Silverlight-based, so I've never used it much.) At this point, I'll have the knowledge to guess whether other works by the same author might be relevant, and at this point I'll do author-specific searches, or search for later papers by other authors that cite an interesting one.
Good surveys are of particular interest, if they can be found, as they're likely to have a high density of good references as well as to be cited by other researchers working in the same area. Often, I'll want to chase down a large proportion of the cited papers in a good survey. If particular conferences or journals are found that are highly relevant, slogging through the ToCs on the publisher's website is often another way to find useful connections.
I prefer an assembly-line approach: I don't want to actually read papers while trawling; I don't want to chase references while reading.
If I click on a paper title in the search results, the most important thing I want to see on the next screen is not the paper title; it's everything else about the paper that will let me figure out how much additional attention it's worth to me. If I've deliberately looked up the paper, that's when I want to surf a citation graph, or explore other works by the same author.
The process is very messy and only partially automatable. But, any new search site would have to provide a lot of value relative to Google Scholar in order to result in a real improvement to the overall workflow.
http://academic.research.microsoft.com/
Example author page:
http://academic.research.microsoft.com/Author/1180211/hari-b...
Example citation graph:
http://academic.research.microsoft.com/VisualExplorer#118021...
Coauthor graph:
http://academic.research.microsoft.com/VisualExplorer#118021...
And finally, the most addictive feature, coauthor path:
http://academic.research.microsoft.com/VisualExplorer#118021...
Google Scholar and MSN Academic both have ways of trying to deal with this. Interestingly, both often get you to a copy from the extensive number of "a professor illegally posted a PDF on the public web even though the publisher holds copyright and wouldn't allow that" copies. Google Scholar also will try to let you register your academic affiliation as a 'preference' and use the academic institution's infrastructure to get you to a post-authenticated licensed copy.
scholar.ly... doesn't seem to do this all that well.
I'm surprised that dude_abides thinks MSN Academic is 'light years better than Google Scholar', hasn't been my experience.
(I happen to work in the field we're talking about, being a software developer for a university library)
I spoke to two CS professors who had interesting views. The first told me he "knew everyone", and that the tool wasn't worth his time- the second said that he "thought he knew everyone", but had a great use regardless. He wanted his students and peers to try it so that they could learn the movers in his part of computer science, and take over the conference he'd been organizing.
Just another possible source of ideas.
Also I would recommend adding a meta image of your icon on at least the index page, because the only images available for preview when sharing on Facebook are pictures of the developers.[1]
* browse the citation and co-authorship graphs without jumping between PDFs.
* find authors relevant to your searches- when we do our job right, serendipitously.
I think many of our future features are going to hew closely to "there's power in people".
Searching for paper title 'Morality as a System of Hypothetical Imperatives' doesn't return the paper or author.
Searching for keywords 'Democratic Authority' returns unrelated CS, engineering, and risk management results but no philosophy or political science results.
Searching for author wasn't effective - top hit for 'AJ Simmons' was 'Jennifer Pealer M. A'
Lots of gobbledigook in the results > ⌊aj⌋xj + fj≤f0 > expand > > 2007 > > n� j=1 ajxj + Substitute aj = ⌊aj ⌋ + fj, b = ⌊b ⌋ + f0. Then,
So all up, not very promising from my initial perspective and as a user, I see no clear advantage over GS.
The think that academic search seems to lack right now is the ability to follow citations easily. In early stage research, I would love to be able enter a keyword eg 'Philosophical anarchism' and follow the citation trail but limited to that keyword eg show citing papers based on their impact AND keyword match.
What about following keywords in Scholrly doesn't satisfy what you need?
http://scholr.ly/results/?q=bayesian+epistemology&x=0... http://scholar.google.com.au/scholar?q=bayesian+epistemology...
Scholrly omits big names like Hartmann and Talbott. Most of the author section is actually filled with non-people.
The publications section doesn't show me citation count or any reason why it might be relevant such as keyword highlights or score. I'd have a very hard time trusting these results that have such clear omissions.
'Causal Inference' at least includes Judea Pearl as a top hit but clicking the link http://scholr.ly/paper/1147771/the-mathematics-of-causal-inf... sends me to a page that is 80% white space and not very informative.
Then compare http://scholar.google.com.au/citations?user=bAipNH8AAAAJ&... with http://scholr.ly/person/5080037/judea-pearl
Why do I want to look at an empty page with a picture of an owl? (Pearl by the way is a rockstar CS professor with 400+ papers and nearly 50k citations - you list a single paper of his)
My biggest pain point of academic search is knowing where I should spend my limited time researching. GS does an OK job of pointing me in the right direction but scholrly wastes my time with numerous dead ends.
I'd love to include results from philosophy and related fields, but we just don't have data sources for them yet. Right now, I think we need to do a better job hammering in that the data we've indexed is in the computer and information science arena. We don't have the resources of all the other players in the field, so I think a niche strategy is important. Are there any particularly great repositories for bibliographic or full-text data in philosophy?
On Judea Pearl- you're right, we messed up! Do consider, though, that he's claimed his Google Scholar Citations profile. We've done all of our profile inference automatically. Sometimes that leads to a bunch of author pages that need to be merged, like in Pearl's case- we have all his papers, but didn't know they were written by the same real-world person, so they're fragmented (http://scholr.ly/results/?q=judea+pearl&x=0&y=0&...). Other times, we have more complete profiles than Google, because many academics don't claim their Google Scholar Citations profiles.
It's an ongoing concern, so we'll be spending a bunch of time on this problem (called entity disambiguation in the lit) as well as upgrading venues, publishers, etc to clickable first-class citizens before our next major release.
Thanks so much for your feedback- hopefully I'll be able to post again soon with improvements.